#Amazon BI tools

[vuelitics1]

Discover how the world’s top companies are leveraging Business Intelligence (BI) to stay ahead of the competition! In this video, we break down the strategies and tools used by giants like Google, Amazon, Apple, and more to optimize operations, enhance customer experience, and drive innovation. From real-time data analysis to predictive analytics, these companies are transforming the way business is done.

Whether you’re a business owner, a data enthusiast, or just curious about how big brands like Netflix and Tesla use BI to gain a competitive edge, this video is a must-watch. Learn how Business Intelligence tools like Tableau, Microsoft Power BI, and SAP BusinessObjects are being used to make smarter decisions, predict customer behavior, and streamline operations.

Visit Our Webiste: https://vuelitics.com/

[jcmarchi]

10 Best AI Tools for Retail Management (December 2024)

New Post has been published on https://thedigitalinsider.com/10-best-ai-tools-for-retail-management-december-2024/

10 Best AI Tools for Retail Management (December 2024)

AI retail tools have moved far beyond simple automation and data crunching. Today’s platforms dive deep into the subtle patterns of consumer behavior, market dynamics, and operational efficiency – finding hidden opportunities that even experienced retailers might miss. What makes these tools particularly useful is their ability to process millions of micro-decisions simultaneously, from optimal shelf placement to precise inventory timing, creating a level of retail orchestration that was previously impossible.

In this guide, we will explore some AI tools that are reshaping how modern retail operates, each bringing its own specialized intelligence to solve complex retail challenges.

Kimonix is an AI merchandising platform that processes eCommerce data to optimize product placement and boost sales. The platform’s AMS (Advanced Merchandising Strategy) engine analyzes multiple retail metrics simultaneously – from sales performance to inventory levels and customer behavior patterns – to make smart merchandising decisions in real-time.

The AI engine connects directly with Shopify’s admin interface, requiring no coding while constantly syncing with store analytics. It creates dynamic product collections by processing sales metrics, inventory status, and customer insights, automatically adjusting product placements to maximize revenue. The system runs continuous A/B tests on collection strategies, selecting winning combinations based on performance data.

Key features:

AI collection management with real-time optimization

Multi-parameter product sorting based on sales, inventory, and margin data

Automated A/B testing for strategy validation

1:1 product recommendations across store pages

Email marketing integration with automated landing pages

Visit Kimonix →

Stackline is an AI retail intelligence platform that processes data from over 30 major retailers to optimize eCommerce performance. The platform analyzes shopper behavior, marketing metrics, and operational data across 26 countries, helping over 7,000 global brands make smarter retail decisions.

The platform’s Shopper OS acts as the AI’s primary analysis center, processing first-party customer data from multiple retailers simultaneously. The AI system tracks real-time metrics – from sales patterns to search rankings – while connecting purchase behaviors directly to advertising campaigns through its Amazon partnership. This multi-retailer attribution system gives brands clear insights into how their marketing efforts drive sales across different channels.

The Beacon platform sits at the core of Stackline’s AI capabilities, unifying data streams from four key areas: shopper insights, marketing performance, operational metrics, and competitive intelligence. The AI processes this information to generate automated forecasts and scenario planning, while simultaneously monitoring digital shelf presence and optimizing retail media campaigns across marketplaces.

Key features:

Multi-retailer customer data processing system with direct messaging capabilities

Real-time analytics engine tracking sales and search performance

Cross-channel attribution system with Amazon advertising integration

AI-powered forecasting and scenario planning tools

Automated content generation for product listings

Visit Stackline →

Image: Crisp

Crisp Data Platform is an AI system that processes retail data from over 40 retailers and distributors to give CPG (Consumer Packaged Goods) brands comprehensive control over their retail operations. The AI analyzes and standardizes diverse data streams – from inventory levels to consumer purchases – creating a unified view of retail performance.

The platform’s AI begins by cleaning and normalizing data from multiple sources into consistent schemas. This allows for both detailed analysis of individual retailers and broad national-level insights. The system processes data through specialized Commerce APIs that handle everything from chargeback disputes to purchase order generation, while maintaining strict data governance through controlled access to specific categories, products, and stores.

The AI’s data processing extends into advanced analytics, enabling brands to track consumer purchases across multiple channels while linking them to advertising campaigns. The system continually replicates this information into existing data lakes or warehouses, powering generative AI features that produce deeper retail insights. Through integration with Microsoft Azure, Databricks, and various BI tools, the AI maintains seamless connections with third-party applications for forecasting and financial planning.

Key features:

Multi-source data processing system with 40+ retail integrations

Commerce API framework for automated retail operations

Cross-channel attribution system with campaign tracking

AI-powered analytics engine with customizable dashboards

Automated data replication with warehouse integration

Visit Crisp →

ScanUnlimited is an AI analysis platform that processes up to 300,000 Amazon products per hour, helping sellers find profitable inventory opportunities. The AI scans massive product catalogs – up to 30,000 items per scan – through multiple data formats including UPC, ASIN, EAN, and ISBN.

The AI’s core analysis engine calculates profit potential through a proprietary sales estimation algorithm, specifically tuned for the US Amazon marketplace. It processes multiple data points simultaneously: current market prices, competitor positions, fulfillment fees, and currency exchange rates across 200+ global currencies. The system also runs continuous restriction checks, alerting sellers to potential IP compliance issues before inventory investment.

The platform’s data visualization system processes historical price trends through three distinct Keepa charts, showing 30, 90, and 365-day patterns. For each product, the AI analyzes competitive dynamics, including Buy Box ownership and market positioning, while identifying special inventory considerations like Small & Light eligibility and hazmat requirements.

Key features:

High-speed product scanning engine with multi-format support

Sales estimation algorithm with profit calculation system

Real-time restriction checking with IP compliance alerts

Multi-timeframe historical analysis tools

Competitive position tracking with Buy Box monitoring

Visit ScanUnlimited →

Triple Whale is an AI data analysis platform that integrates all Shopify store data streams – from marketing metrics to inventory levels – into a single intelligent system. Triple Whale’s AI processes information from multiple sources including Shopify, Google Analytics, and advertising platforms to give merchants clear insights for smarter decisions.

At the core of Triple Whale sits its proprietary Triple Pixel technology, which analyzes first-party customer data to decode the full purchasing journey. The AI examines every touchpoint in the customer experience, measuring how different marketing channels influence sales through its Total Impact Attribution model. This enables merchants to see precisely how their marketing spend translates into actual revenue.

Beyond marketing insights, the platform’s AI assistant “Willy” continually monitors store performance, spotting unusual patterns and potential issues before they impact sales. The system analyzes inventory movements in real-time, connects with shipping partners like ShipBob and ShipStation, and alerts merchants when promotional items risk going out of stock.

Key features:

Multi-source data integration with real-time analytics processing

Triple Pixel tracking system for purchase journey analysis

AI anomaly detection with automated alerts

Real-time inventory monitoring with logistics integration

Customer segmentation engine with lifetime value tracking

Visit Triple Whale →

Syndigo is an AI content engine that keeps product information accurate and engaging across countless retail channels. The platform’s AI analyzes and enriches product content – from basic specifications to rich media – ensuring shoppers always see compelling, accurate information no matter where they browse.

The AI’s product information management system goes beyond simple data storage. By applying SmartPrompts technology and integrating with ChatGPT, the AI transforms basic product details into rich, SEO-optimized descriptions that drive sales. When content needs updating, the system automatically propagates changes across all connected platforms, maintaining consistency whether customers shop on Amazon, Walmart, or specialty retailers.

The VendorSCOR tool represents the AI’s analytical core, continuously monitoring product content quality across the digital shelf. The system grades every product page, identifying gaps and opportunities while automatically instructing suppliers on specific improvements. This intelligent audit process ensures product content not only meets technical requirements but resonates with shoppers through vivid imagery and interactive experiences.

Key features:

AI content generation system with ChatGPT integration

Multi-format syndication engine supporting GDSN, ACES, and PIES standards

Automated content grading with improvement instructions

Rich media management system for visual content

Real-time analytics engine for product performance tracking

Visit Syndigo →

Image: Trendalytics

Trendalytics is an AI engine that decodes retail by analyzing millions of signals across social media, search patterns, and market data. It helps brands spot the next big trend before it hits mainstream, turning the complex web of consumer behavior into clear, actionable insights.

The AI’s trend analysis capabilities run deep. By processing visual content, social conversations, and shopping patterns simultaneously, the system builds intricate models of trend lifecycles. Each potential trend is tracked, giving retailers foresight into what’s next.

Beyond simple trend-spotting, the AI acts as a market intelligence hub. It analyzes competitor strategies by dissecting their product mix, pricing approaches, and visual merchandising choices. This competitive insight combines with deep consumer behavior analysis, creating a rich understanding of not just what’s selling, but why it resonates with shoppers.

Key features:

Multi-channel trend detection system with lifecycle tracking

Visual recognition engine for product and style analysis

Competitive intelligence processing with price monitoring

Consumer behavior analysis framework

Predictive analytics engine for trend forecasting

Visit Trendalytics →

RetailAI360 is an analytics system that processes retail data streams to optimize operations and predict market changes. The AI analyzes real-time data across inventory, sales, and customer behavior to help retailers make faster, smarter decisions.

The system’s core engine processes three main data categories simultaneously: inventory metrics, customer interactions, and sales channel performance. For inventory, the AI monitors stock levels and generates automated reorder alerts. In customer analysis, it tracks browsing patterns and purchase histories to reveal emerging preferences. The system also unifies data from physical stores, online platforms, and mobile apps to create comprehensive performance insights.

The AI’s processing capabilities extend to predictive analytics, using historical patterns to forecast future trends and demand. This helps retailers shift from reactive to proactive management, particularly in inventory optimization and customer engagement strategies.

Key features:

Real-time analytics engine with instant alert capabilities

Multi-channel behavior analysis system

AI-powered inventory optimization tools

Predictive trend detection framework

Automated report generation with visual insights

Visit RetailAI360 →

LEAFIO AI is a retail management system that organizes inventory, store layouts, and supply chains through intelligent automation. The AI works across every retail level – from individual store shelves to warehouse distribution – creating a unified approach to retail optimization.

The platform’s inventory intelligence stands out through its self-regulating algorithms. When market conditions shift, the AI adapts its replenishment patterns automatically, maintaining optimal stock levels even during unpredictable periods. This dynamic response system connects directly to store cameras, using image recognition to spot empty shelves instantly and trigger smart restocking protocols.

The AI brings the same precision to store layouts. Its planogram optimization system analyzes customer flow patterns and product relationships, suggesting space arrangements that boost sales while maintaining operational efficiency. The system processes both macro store layouts and micro-shelf arrangements, ensuring every product finds its optimal position.

Key features:

Self-learning demand forecasting engine

Real-time shelf monitoring with image recognition

Multi-level supply chain optimization system

Dynamic planogram management tools

Cloud-based analytics dashboard

Visit LEAFIO →

ContactPigeon is an AI customer engagement platform that analyzes shopping behavior across multiple channels to create deeper connections between retailers and their customers. The system processes diverse data streams – from website interactions to purchase histories – building rich customer profiles that power personalized marketing.

The AI’s brain constantly analyzes and adapts to customer signals. When someone browses products, opens emails, or interacts with chat messages, the AI absorbs these behaviors into its understanding. This creates a dynamic feedback loop where each customer interaction makes future communications more relevant and engaging. The system runs automated workflows that respond to specific customer actions, from cart abandonment to post-purchase follow-ups.

The platform’s omnichannel communication system orchestrates personalized messages across email, SMS, push notifications, and Facebook Messenger. The AI determines optimal timing and channel selection for each message, while a specialized retail chatbot handles customer support inquiries.

Key features:

Real-time behavior analysis engine with predictive capabilities

Multi-channel messaging system with AI-optimized delivery

Automated workflow engine for customer journey management

AI chatbot designed for retail support scenarios

Dynamic segmentation tools with behavior-based targeting

Visit ContactPigeon →

Transforming Retail Management Through AI

These top AI retail management platforms embody a fundamental change in how retailers approach their operations. Each tool tackles specific challenges: Kimonix optimizes product placement, Stackline decodes market intelligence, Crisp streamlines CPG operations, while platforms like Trendalytics predict tomorrow’s trends. Together, they form a comprehensive toolkit that enables retailers to process and act on data at unprecedented speeds and scales.

The future of retail clearly belongs to those who can leverage AI’s analytical power effectively. As these platforms continue to evolve, we will see even deeper integration between different retail functions – from inventory management to customer engagement. By embracing these AI tools, retailers are not just keeping pace with change – they are actively shaping the future of commerce.

[bfpnola]

I am not Palestinian nor am I Jewish. Be that as it may, I hate settler colonialism, even more so as a brown, bi, genderqueer ‘Afab’ person. I just wanted to say. 1) your post on the topic is more empathetic and insightful than I’ve seen a lot of people be about this over my entire life and I’ve asked questions of both sides, I tend to stay out of the fray cause I don’t feel it my place to speak over Palestinians and Jews (who are critical of Israel). But, do you have any advice for being a better ally to Palestinians and combating anti-semitism and anti Jewish racism in the everyday?

hey sweetheart! thank you for your commitment to the movement and your earnestness. i am not Palestinian or Jewish either, so i did what is always considered best: i asked those who are! that's exactly why our Advocacy Committee within BFP exists :)

from one of our Palestinian youth volunteers:

if you have the money to do so, donate to the cause! the unfortunate truth is that to gain access to various resources, things cost money. more specifically, donate to humanitarian aid funds you've done the research for and are sure are doing work on the ground. even better if you can donate directly to those being affected! this includes Palestinians on the ground but also within the diaspora who need self care items, especially for all the work they've been doing educating others. for example, this is an organization this member volunteers with and trusts:

and these are two amazon lists of Palestinian youth within the diaspora:

share posts by Palestinians! the big thing is really just getting the word out, sharing their perspective. Zionist propaganda is hard to penetrate so the least we can do is uplift their voices by sharing!

from one of our Jewish youth volunteers:

understand that not all Jewish people are Zionists and not all Zionists are Jewish. saying the two are equivalent is not only antisemitic but ignores the blatant statistics, like the growing number of anti-Zionist Jewish young adults in the united states for example, or the fact that the biggest supporters of israel are actually evangelicals.

to that same point, know that israel has been purposefully trying to conflate the two in order to then label anyone who does critique the state as automatically antisemitic. it is a tool.

additionally, be careful with the rhetoric you choose to spread & subscribe to (i.e., watch how they describe israel. do they refer to the people as Jews or Zionists? it can tell you a lot about how educated they are and their vague stance on the matter)

my own additions as a longstanding ally and friend of those involved:

learn your history! there is a clear attempt to distort the history of Palestine. learn what Palestine was like before israel's occupation. learn about the way pioneering Zionists openly called Zionism "colonialism" and didn't even try to hide it. learn about how discussions of the Zionist project were discussed roughly 80 years before the Holocaust ever happened. this does not mean that some Jews did not, in fact, move to Palestine in response to such a horrific event, but in the words of a Jewish mutual of mine, israel's rhetoric literally weaponizes Jewish trauma by conflating these two dates in history.

BDS movement! stands for boycott, divestment, and sanctions!

when possible, actually speak to people of Palestinian descent. like seriously. posts are great, but actually speaking to people who are knowledgeable in real time can be so helpful for getting your questions addressed, so long as you are respectful, of course. a great place to do this, not even to advertise, is actually our Discord server linked in our bio @bfpnola

know that language matters, as inconsequential as it may seem. in the words of my Palestinian, Kashmiri, and Artsakhi friends and/or mutuals, when speaking of occupations, we capitalize the occupied people's country (ex. Palestine) while not doing so for the occupier's (ex. israel) to delegitimize them.

learn about Hamas and its history/purpose. here are my notes on two podcast episodes let by Palestinians:

thank you for your ask! im sure i may think of other things later but these are my answers for now.

-- reaux (she/they)

[jitendrarathod]

"Unlocking Business Intelligence with Data Warehouse Solutions"

Data Warehouse Solution: Boosting Business Intelligence

A data warehouse (DW) is an organized space that enables companies to organize and assess large volumes of information through multiple locations in a consistent way. This is intended to assist with tracking, company analytics, and choices. The data warehouse's primary purpose was to render it possible to efficiently analyze past and present information, offering important conclusions for management as a business strategy. 

A data warehouse normally employs procedures   (Take, convert, load) for combining information coming from several sources, including business tables, operations, and outside data flows.This allows for an advanced level of scrutiny by ensuring data reliability and precision. The information's structure enables complicated searches, which are often achieved using the aid of SQL-based tools, BI (Business Intelligence) software, or information display systems.

Regarding activities requiring extensive research, data storage centers were ideal since they could provide executives with rapid and precise conclusions. Common application cases include accounting, provider direction, customer statistics, and projections of sales. Systems provide connectivity, speed, and easy control of networks, but as cloud computing gained popularity, data warehouses like Amazon's Redshift, Google's Large SEARCH, and Snowflake have remained famous.  

In conclusion, managing information systems is essential for companies that want to make the most out of their information. Gathering information collected in one center allows firms to better understand how they operate and introduce decisions that promote inventiveness and originality.

[womaneng]

Data Science

📌Data scientists use a variety of tools and technologies to help them collect, process, analyze, and visualize data. Here are some of the most common tools that data scientists use:

👩🏻‍💻Programming languages: Data scientists typically use programming languages such as Python, R, and SQL for data analysis and machine learning.

📊Data visualization tools: Tools such as Tableau, Power BI, and matplotlib allow data scientists to create visualizations that help them better understand and communicate their findings.

🛢Big data technologies: Data scientists often work with large datasets, so they use technologies like Hadoop, Spark, and Apache Cassandra to manage and process big data.

🧮Machine learning frameworks: Machine learning frameworks like TensorFlow, PyTorch, and scikit-learn provide data scientists with tools to build and train machine learning models.

☁️Cloud platforms: Cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure provide data scientists with access to powerful computing resources and tools for data processing and analysis.

📌Data management tools: Tools like Apache Kafka and Apache NiFi allow data scientists to manage data pipelines and automate data ingestion and processing.

🧹Data cleaning tools: Data scientists use tools like OpenRefine and Trifacta to clean and preprocess data before analysis.

☎️Collaboration tools: Data scientists often work in teams, so they use tools like GitHub and Jupyter Notebook to collaborate and share code and analysis.

For more follow @woman.engineer

[techniktagebuch]

2024

Mein Medien-Menü: Zwölf Jahre später

Im Februar 2012 habe ich für Christoph Kochs Reihe "Mein Medien-Menü" beschrieben, wie meine Mediennutzung damals aussah. Diese Serie ist einer der Gründe, warum es das Techniktagebuch gibt. Bis November 2014 sind insgesamt 89 Folgen im Blog von Christoph Koch erschienen. Danach zog das Medienmenü um zu Krautreporter, wo es so aussieht, als seien bis ungefähr 2017 noch mal ziemlich viele Folgen veröffentlicht worden. Ob man die gesammelt irgendwo lesen kann und ob es nach 2017 noch weiterging, weiß ich nicht, weil ein Krautreporter-Abo nicht zu meiner Mediennutzung gehört. (Ohne besondere Gründe, im ersten Krautreporterjahr war ich Unterstützerin. Ich erinnere mich vage an Unzufriedenheit, weshalb ich es danach nicht mehr war. Aber die Details sind leider undokumentiert geblieben.)

Ich habe lange nicht mehr an diesen Bericht gedacht und sehe heute noch mal nach, wie das eigentlich 2012 war und was sich geändert hat.

"Goodreads ist nicht besonders überzeugend, ich kenne nur wenige Menschen, die es nutzen, und die Buchempfehlungen dort sind nur unwesentlich besser als bei Amazon. Aber ich finde es sehr hilfreich, um eine realistische Vorstellung von meinem Leseverhalten zu bekommen. Bis ich damit anfing, hielt ich mich immer noch für denselben Leser wie 1995."

Ich war damals noch ein Leser und keine Leserin. Mit dem generischen Maskulinum habe ich erst viel später aufgehört. Im Techniktagebuch ist zu sehen, wann das passiert ist, meiner Erinnerung nach vielleicht 2018? Irgendwann sehe ich nach und dann steht es hier genauer. Goodreads fand ich zwischen damals und jetzt sehr überzeugend. Ich kenne zwar immer noch nur wenige Menschen, die es nutzen, und in die automatischen Buchempfehlungen habe ich schon lange nicht mehr reingesehen. Aber ich habe dort in den letzten Jahren sehr viele Rezensionen gelesen und das war der Hauptweg, auf dem ich zu neuen Büchern gefunden habe. Allerdings versuche ich gerade, mich (wegen der Amazon-Zugehörigkeit) von Goodreads zu lösen zugunsten von StoryGraph. Da läuft aber gerade erst der Umzug meiner Daten und ich kann noch nichts dazu sagen.

"Meine Papierbücher habe ich in den letzten paar Jahren mit Hilfe des Berliner Büchertischs stark reduziert, von ungefähr zwölf mehrreihig gefüllten Billyregalen bin ich jetzt runter auf sieben halbvolle."

Im Moment sind es vier ganz volle, davon zwei mehrreihig gefüllt. 2019 waren es auch schon nur vier. Was mit den drei anderen passiert ist, weiß ich nicht mehr. Falls es Zuwachs gegeben hat, ist das unfreiwillig passiert, durch eigene Belegexemplare, ungefragt zugeschickte Bücher und Bücher, die ich auf Papier kaufen musste, weil ich sie für die Arbeit brauchte und nicht auf einem digitalen Weg beschaffen konnte. Ich lese jetzt aber viel mehr Bücher als 2012.

Dann geht es im Text von 2012 einen Absatz lang um RSS-Feedreader. Ich habe damals noch den Google Reader genutzt, den Google anderthalb Jahre später eingestellt hat. Mit Feedly, dem Tool, mit dem ich ihn ab Mitte 2013 zu ersetzen versuchte, bin ich nie so richtig warm geworden, er ist 2016 aus meinem Leben verschwunden. Ich habe ihn nicht ersetzt und lebe seitdem feedreaderlos.

"... das, was ich im Netz lese, speist sich jetzt ungefähr (geraten und nicht gemessen, kann also auch ganz anders sein) zur Hälfte aus dem Feedreader und zur Hälfte aus dem Bekanntenkreis via Google+, Twitter und Facebook. "

"Netz" sage ich nicht mehr, seit ich 2021 erfahren habe, dass es ein altmodisches Wort für Internet ist. Ich dachte bis dahin, es sei umgekehrt.

"Ein oder zwei Jahre lang hatte ich mir für die wichtigsten Feeds eine Weiterleitung nach Twitter gebastelt (via Yahoo Pipes und Twitterfeed), aber seit es Google+ gibt, nutze ich Twitter viel weniger und sehe deshalb auch diese Weiterleitung kaum mehr."

Yahoo Pipes! Das war wirklich schön und ich vermisse es heute noch manchmal. Es wurde 2015 eingestellt. Man konnte damit, so ähnlich wie jetzt mit Zapier, andere Internetdinge zusammenstecken, aber mit einer schönen grafischen Oberfläche. Bei Google+ war ich 2011 und offenbar auch noch Anfang 2012 sehr aktiv, aber irgendwann bald danach war es wieder vorbei. Warum, weiß ich nicht mehr, es ist im Techniktagebuch nicht dokumentiert. In meiner Erinnerung wurde Google+ kurz nach dem Start wieder stillgelegt, aber das scheint nicht zu stimmen, in der Wikipedia steht: Schließung 2019. Ich bin danach zu Twitter zurückgekehrt.

Von den Blogs, die mir damals wichtig waren, gibt es ein paar noch, sie sind mir aber unsympathisch geworden (Marginal Revolution, Less Wrong, Overcoming Bias). Andere gibt es nicht mehr (Stefan Niggemeiers Blog, Penelope Trunk). Ich glaube, dass das nicht weiter besorgniserregend ist, die meisten Blogs haben eine begrenzte Lebenszeit aus inhaltlichen wie aus Verfügbare-Lebenszeit-Gründen und es wachsen ja auch wieder neue nach. Im Überschneidungsbereich von "existiert noch" und "wir haben uns nicht weltanschaulich entfremdet, glaube ich", liegt nur ein einziger der erwähnten Blogs: O'Reilly Radar. Ich lese es trotzdem nie. Das hat auch wieder mit dem Verschwinden des Google Readers zu tun. Ich lese wahrscheinlich immer noch so viel in Blogs wie früher, aber nicht mehr regelmäßig in denselben, sondern eben die Beiträge, die mir bis 2022 Twitter heranspülte und seit meinem Umzug Mastodon. Ich merke mir dann nicht, in welchem Blog die standen, und könnte keine Blognamen nennen. Facebook erwähne ich 2012 noch, 2015 habe ich das Facebook-Browsertab geschlossen und 2017 die App vom Handy gelöscht.

Zeitschriften mit der Post bekam ich 2012 noch mehrere, zum Teil wegen Vereinsmitgliedschaften und zum Teil, weil ich sie abonniert hatte. Eins der Abos habe ich gleich nach der Dokumentation im Medien-Menü-Beitrag gekündigt, ein anderes endete etwas später von allein, und die Mitgliedszeitschriften haben sich in den letzten Jahren entweder selbst auf nur-noch-digital umgestellt oder ich habe darum gebeten, nichts mehr auf Papier zu bekommen. Außerdem wird meine Post seit mehreren Jahren direkt an Nathalie weitergeleitet, die sich um meine Papierverwaltung kümmert.

2024 gehört zur finanziellen Seite meines Medien-Menüs, dass ich einige Leute regelmäßig unterstütze bei Patreon, Steady und ähnlichen Plattformen. Ich müsste das mal in einem gesonderten Beitrag genauer aufschreiben, jedenfalls ist es im Moment der Hauptkanal, auf dem Geld von mir zu Kulturschaffenden fließt. Die Newsletter oder Videos, die zu manchen dieser Abos gehören, schaue ich mir aber eigentlich nie an. Es geht mehr ums Prinzip, ich möchte, dass diese Leute weiter Videos machen, Bücher schreiben oder was sie halt so tun.

"Radio habe ich seit den 80er Jahren nicht mehr gehört (traumatische Schulbus-Erlebnisse mit Bayern 3). Eine Tageszeitung hatte ich zuletzt um 1990 im Abonnement. Ich habe aufgehört, fernzusehen, als im deutschen Kabel das britische MTV Europe durch den deutschen Ableger ersetzt wurde, das muss so um 1995 herum gewesen sein. Über Hörbücher und Podcasts weiß ich nichts, ich schlafe aus technischen Gründen beim Zuhören immer sofort ein."

Daran hat sich seit 2012 wenig geändert. Ich war viel im Haushalt meiner Mutter, und dort wird jeden Tag wenigstens eine Stunde Radio gehört (BR Heimat zwischen 22:00 und 23:00). Außerdem ist es mir gelungen, mittelgroße Teile des "Drinnies"-Podcasts zu hören. Eine Änderung meines Mediennutzungsverhaltens sehe ich darin aber nicht, das eine ist Zufall, das andere eine Ausnahme.

Video kommt im Text von 2012 gar nicht vor. Hier hat sich mehr geändert, 2016 habe ich eingesehen, wozu YouTube gut ist, und inzwischen nutze ich es oft, allerdings vor allem in der kleinen Vorschau-Ansicht auf dem Handy, die ungefähr 6x4 cm groß ist, und ohne Ton. Theoretisch folge ich dort zwar ein paar Leuten aus den Bereichen Handwerk (Schreinerei, Metallbearbeitung, Rohrreinigung) und Schlittenhundehaltung, praktisch mache ich davon aber so gut wie nie Gebrauch, es sind Höflichkeits-Abos zur Erfreuung der Youtuber*innen. Ich bin nur da, wenn ich was Bestimmtes suche und gucke dann vielleicht noch ein paar von den Dingen, die YouTube mir vorschlägt. Dabei bin ich inzwischen besser darin geworden, den Vorschlägen zu widerstehen, weil mir YouTube immer gern Katastrophen und Unglücke zeigen möchte und ich aber wirklich nicht noch mehr über scheußliche Tode beim Höhlentauchen wissen will. Lieber würde ich das vorhandene Wissen darüber wieder aus meinem Kopf löschen lassen. Was mir in meinem Medienmenü 2024 fehlt, ist ein Lösch-YouTube zur Entfernung von Informationen.

(Kathrin Passig)

[raziakhatoon]

 Data Engineering Concepts, Tools, and Projects

All the associations in the world have large amounts of data. If not worked upon and anatomized, this data does not amount to anything. Data masterminds are the ones. who make this data pure for consideration. Data Engineering can nominate the process of developing, operating, and maintaining software systems that collect, dissect, and store the association’s data. In modern data analytics, data masterminds produce data channels, which are the structure armature.

How to become a data engineer:

 While there is no specific degree requirement for data engineering, a bachelor's or master's degree in computer science, software engineering, information systems, or a related field can provide a solid foundation. Courses in databases, programming, data structures, algorithms, and statistics are particularly beneficial. Data engineers should have strong programming skills. Focus on languages commonly used in data engineering, such as Python, SQL, and Scala. Learn the basics of data manipulation, scripting, and querying databases.

 Familiarize yourself with various database systems like MySQL, PostgreSQL, and NoSQL databases such as MongoDB or Apache Cassandra.Knowledge of data warehousing concepts, including schema design, indexing, and optimization techniques.

Data engineering tools recommendations:

    Data Engineering makes sure to use a variety of languages and tools to negotiate its objects. These tools allow data masterminds to apply tasks like creating channels and algorithms in a much easier as well as effective manner.

1. Amazon Redshift: A widely used cloud data warehouse built by Amazon, Redshift is the go-to choice for many teams and businesses. It is a comprehensive tool that enables the setup and scaling of data warehouses, making it incredibly easy to use.

One of the most popular tools used for businesses purpose is Amazon Redshift, which provides a powerful platform for managing large amounts of data. It allows users to quickly analyze complex datasets, build models that can be used for predictive analytics, and create visualizations that make it easier to interpret results. With its scalability and flexibility, Amazon Redshift has become one of the go-to solutions when it comes to data engineering tasks.

2. Big Query: Just like Redshift, Big Query is a cloud data warehouse fully managed by Google. It's especially favored by companies that have experience with the Google Cloud Platform. BigQuery not only can scale but also has robust machine learning features that make data analysis much easier. 3. Tableau: A powerful BI tool, Tableau is the second most popular one from our survey. It helps extract and gather data stored in multiple locations and comes with an intuitive drag-and-drop interface. Tableau makes data across departments readily available for data engineers and managers to create useful dashboards. 4. Looker:  An essential BI software, Looker helps visualize data more effectively. Unlike traditional BI tools, Looker has developed a LookML layer, which is a language for explaining data, aggregates, calculations, and relationships in a SQL database. A spectacle is a newly-released tool that assists in deploying the LookML layer, ensuring non-technical personnel have a much simpler time when utilizing company data.

5. Apache Spark: An open-source unified analytics engine, Apache Spark is excellent for processing large data sets. It also offers great distribution and runs easily alongside other distributed computing programs, making it essential for data mining and machine learning. 6. Airflow: With Airflow, programming, and scheduling can be done quickly and accurately, and users can keep an eye on it through the built-in UI. It is the most used workflow solution, as 25% of data teams reported using it. 7. Apache Hive: Another data warehouse project on Apache Hadoop, Hive simplifies data queries and analysis with its SQL-like interface. This language enables MapReduce tasks to be executed on Hadoop and is mainly used for data summarization, analysis, and query. 8. Segment: An efficient and comprehensive tool, Segment assists in collecting and using data from digital properties. It transforms, sends, and archives customer data, and also makes the entire process much more manageable. 9. Snowflake: This cloud data warehouse has become very popular lately due to its capabilities in storing and computing data. Snowflake’s unique shared data architecture allows for a wide range of applications, making it an ideal choice for large-scale data storage, data engineering, and data science. 10. DBT: A command-line tool that uses SQL to transform data, DBT is the perfect choice for data engineers and analysts. DBT streamlines the entire transformation process and is highly praised by many data engineers.

Data Engineering  Projects:

Data engineering is an important process for businesses to understand and utilize to gain insights from their data. It involves designing, constructing, maintaining, and troubleshooting databases to ensure they are running optimally. There are many tools available for data engineers to use in their work such as My SQL, SQL server, oracle RDBMS, Open Refine, TRIFACTA, Data Ladder, Keras, Watson, TensorFlow, etc. Each tool has its strengths and weaknesses so it’s important to research each one thoroughly before making recommendations about which ones should be used for specific tasks or projects.

  Smart IoT Infrastructure:

As the IoT continues to develop, the measure of data consumed with high haste is growing at an intimidating rate. It creates challenges for companies regarding storehouses, analysis, and visualization. 

  Data Ingestion:

Data ingestion is moving data from one or further sources to a target point for further preparation and analysis. This target point is generally a data storehouse, a unique database designed for effective reporting.

 Data Quality and Testing: 

Understand the importance of data quality and testing in data engineering projects. Learn about techniques and tools to ensure data accuracy and consistency.

 Streaming Data:

Familiarize yourself with real-time data processing and streaming frameworks like Apache Kafka and Apache Flink. Develop your problem-solving skills through practical exercises and challenges.

Conclusion:

Data engineers are using these tools for building data systems. My SQL, SQL server and Oracle RDBMS involve collecting, storing, managing, transforming, and analyzing large amounts of data to gain insights. Data engineers are responsible for designing efficient solutions that can handle high volumes of data while ensuring accuracy and reliability. They use a variety of technologies including databases, programming languages, machine learning algorithms, and more to create powerful applications that help businesses make better decisions based on their collected data.

[mightyaphrodytee]

There were a few times in my life when music changed for me—what I responded to changed slowly over time, but yeah, there were definite infusions of NEW that veered off on paths maybe not so well-trodden, but that nonetheless stood out as touchstones in my ~~~dramatic half-whisper~~~ journey through 🎶MUSIC 🎼

1977: Heard the best of what’s now considered “classic rock” as it existed at the time, when it was just called “Rock” or “Heavy Metal” or “Prog.” Bands like Rush, Boston, Yes, Queen, Led Zeppelin, Black Sabbath, Pink Floyd, that didn’t get a lot of airplay on the Top 40 stations I’d exclusively listened to. It was thrilling. I caught up on ten years of ignorance in like, 9 months. But I kinda missed out on punk because of that immersion, thanks to my new besties.

1982: Heard my first indie/alternative (“new wave” to some) music and fell hard. The Cure, The English Beat, Joy Division, Kim Wilde, Elvis Costello, U2, Talking Heads, etc. when we moved to Colorado. The availability of some truly esoteric indie music via the Boulder station KBCO was legendary. We had three or four stations in addition to that one! Spoiled! The eighties, man. R.E.M.!!! The music in the clubs was what was on the radio was what was on MTV—you couldn’t escape it, so this huge subset of the rock-listening population were all listening to the big hits at the same time. Madonna, Dire Straits, The Eurythmics, Prince, Duran Duran, Pretenders, Bon Jovi. EVERYBODY knew the hits of the eighties.

1991: Heard “Smells Like Teen Spirit” on the car radio driving through Austin, and both my companion and I were immediately silenced by that intro, and by the end, we were like “What just happened?” just in total delight/light shock…did he really just scream about a mulatto? Who talks like that in 1991, sir? But we just immediately knew this was gonna be huge, and it was, and then came grunge and grunge-lite for the rest of the decade. Soundgarden, STP, Bush, Incubus, Alice In Chains, Pearl Jam, Nirvana (for such a goddamned short time, it’s insane to look back and realize we had so few years with him!)

For some people, life is unbearable without having their consciousness altered in some way. Drugs being one of those ways.

2003: Heard “Caring Is Creepy” by The Shins on a 4-hour “New Alternative” loop XM Radio had handed out as a free trial. Those songs on that loop woke me up to the possibility of new sounds that hit that same place in me as the best of the 80’s and 90’s. I remember Doves “Pounding”, which was used in an episode of The Consultant on Amazon Prime just this week (I shrieked!), “Silver Spoon” by Bis, “Shapes” by The Long Winters, The Postal Service, Death Cab For Cutie…wish I could remember them all. Bruce Springsteen’s Magic album had a song that was my most played for a few years in the aughts—“Radio Nowhere”, which I first heard on that XM trial loop and loved so much I bought the whole album. On iTunes. Still have it. Saw Garden State, heard “Caring Is Creepy” on the soundtrack (again—i shrieked!), and “New Slang,” and fell for them even harder.

Now I listen to what I used to hate (classic rock), but my fairly narrow preference window means I don’t SAY I listen to classic rock, because except for YouTube, I only listen to Radiohead, some Tool, some Metallica most days.

My life is now just mainly Radiohead with a few dollops of all the songs I’ve loved before, from every decade that rock and roll has been rock and roll with ALL its subgenres, heavy on Tool and Metallica as of late.

I can’t even tell what popular music today even is. It all sounds like video game background to me.

Will you still need me

Will you still feed me

When I’m 64?

[azureai102engineer]

VisualPath offers comprehensive AzureAI Engineer Training in Hyderabad, designed to help you master AI technologies and earn your AI-102 Certification. This hands-on program covers key tools like Matillion, Snowflake, ETL, Informatica, SQL, and more. Learn essential Data Warehouse, Power BI, Databricks, Oracle, SAP, and Amazon Redshift skills. You can study at your own pace with recorded sessions, flexible schedules, and global access. Learn from industry experts and advance your career in the data and AI fields. Call +91-9989971070 for a free demo and start your journey with VisualPath today!

WhatsApp: https://www.whatsapp.com/catalog/919989971070/

Visit Blog: https://azureai1.blogspot.com/

Visit: https://www.visualpath.in/online-ai-102-certification.html

[jcmarchi]

10 Best AI Form Generators (August 2024)

New Post has been published on https://thedigitalinsider.com/10-best-ai-form-generators-august-2024/

10 Best AI Form Generators (August 2024)

Efficient data collection and user engagement are crucial for businesses and organizations. Artificial Intelligence (AI) has disrupted the form-building process, offering innovative solutions that streamline creation, enhance user experience, and provide valuable insights.

This article explores the top AI form generators that are transforming how we design, deploy, and analyze online forms. From natural language form creation to advanced analytics and seamless integrations, these platforms leverage AI to make form building more accessible, efficient, and powerful than ever before. Whether you’re a small business owner, a marketing professional, or an enterprise-level organization, these AI-powered tools offer features that can significantly improve your data collection strategies and workflow automation.

Fillout is an innovative AI-powered form builder that simplifies the process of creating dynamic, interactive forms. By leveraging the power of artificial intelligence, Fillout enables users to generate forms quickly and effortlessly, catering to a wide range of needs without the hassle of manual design. With its user-friendly interface and advanced AI capabilities, Fillout streamlines form creation, making it an ideal solution for businesses and individuals looking to collect data efficiently.

One of the standout features of Fillout is its ability to create forms from simple prompts. Users can describe the form they want, and Fillout’s AI will generate a tailored form based on their requirements. The platform also offers a powerful no-code editor, allowing users to customize their AI-generated forms further, ensuring a perfect fit for their specific needs. Fillout’s AI technology continuously learns and improves, providing users with intelligent suggestions and optimizations to enhance their forms’ performance and user engagement.

Key Features:

Fillout uses AI to create forms based on user prompts, saving time and effort.

The platform’s AI suggests design improvements and optimizations to create engaging, high-converting forms.

It constantly learns and adapts, providing users with increasingly accurate and efficient form-building suggestions.

Integrates with popular third-party apps and platforms, ensuring a smooth workflow and easy data management.

Enables real-time collaboration, allowing teams to work together on form creation and leveraging AI to streamline the process

Visit Fillout →

Jotform is a cutting-edge online form builder that also uses AI to streamline the form creation process. With its user-friendly interface and AI-driven features, Jotform empowers businesses and individuals to create custom forms effortlessly, without the need for coding expertise. By leveraging AI technology, Jotform simplifies data collection, enhances form performance, and delivers a seamless user experience.

Jotform offers its AI Form Generator, which allows users to create forms simply by describing their requirements in natural language. The AI chatbot understands the user’s needs and generates a tailored form with basic fields and customizations, saving time and effort. Jotform’s AI capabilities extend beyond form creation, as it also offers an AI Quiz Generator and an AI Signature Generator, demonstrating its commitment to innovation.

Key Features:

Create custom forms effortlessly by describing your requirements to the AI chatbot.

Jotform’s AI features, such as conditional logic and prefill options, improve form completion rates and user experience.

Collaborates with OpenAI’s ChatGPT for its AI Quiz Generator, ensuring data privacy and security.

Dedicated to expanding its AI capabilities to meet evolving user needs and maintain its competitive edge.

Enables businesses to automate repetitive tasks, streamline workflows, and focus on high-value activities

Visit Jotform →

With the introduction of AI-driven features and the launch of its innovative product, Formless, Typeform is redefining how businesses engage with and gather information from their customers. This AI-powered approach simplifies form creation, enhances user engagement, and delivers a personalized, conversational experience for respondents.

At the forefront of Typeform’s AI innovation is Formless, a product that transcends traditional form structures. Formless creates a dynamic, two-way conversation between businesses and respondents, mimicking human-like interactions. By allowing businesses to train the AI on specific topics, Formless can answer respondents’ questions and provide a tailored experience, adapting to responses and asking relevant follow-up questions.

Typeform’s AI capabilities extend beyond Formless, offering features like question recommendation and optimization to craft well-written, concise questions that boost completion rates. The platform’s Smart Insights tool employs AI to analyze form results, providing user-friendly dashboards with high-level data overviews. Additionally, Typeform’s AI streamlines lead qualification by automatically categorizing respondents based on their answers, ensuring efficient prioritization of high-value leads.

Key Features:

AI-powered product creating dynamic, two-way conversations for personalized experiences.

AI-assisted question optimization for enhanced form completion rates.

AI-driven analysis tool providing user-friendly data dashboards.

Efficient lead qualification through AI-powered response analysis.

Continuous AI development, including workflow automation and natural language data querying.

Visit Typeform →

Formstack is pushing the boundaries of form building by integrating artificial intelligence to create a comprehensive workflow automation solution. Unlike traditional form builders, Formstack’s AI doesn’t just assist in form creation—it transforms the entire data collection and processing lifecycle.

At the core of Formstack’s innovation is its AI-powered workflow designer. This feature analyzes your business processes and automatically suggests optimal form structures and data flows, creating end-to-end solutions rather than isolated forms. For example, it might design a customer onboarding process that seamlessly moves from initial contact form to follow-up surveys and integration with your CRM.

Formstack’s AI also shines in its predictive analytics capabilities. By analyzing historical form data, it can forecast submission patterns, helping businesses prepare for peak times or identify potential drop-offs in engagement. This proactive approach allows companies to optimize their forms and processes continuously, staying ahead of user needs and market trends.

Key Features:

Generates tailored forms based on user prompts.

Allows teams to go from idea to solution quickly, regardless of their technical aptitude.

Suggests well-written and concise questions to enhance form completion rates.

Analyzes form data, identifying patterns and anomalies that provide valuable insights for businesses.

Easily integrate with other business systems, such as CRMs and Formstack Documents, for automatic data population and streamlined workflows.

Visit Formstack →

With its user-friendly interface and AI-driven features, Paperform enables businesses and individuals to create engaging, personalized forms effortlessly, without the need for coding expertise. By leveraging AI technology, Paperform enhances the form-building experience, making it more efficient, intuitive, and tailored to users’ specific needs.

One of Paperform’s standout AI features is its ability to generate forms based on user prompts. Users can simply describe the type of form they need, and Paperform’s AI-powered Form Builder will create a customized form with relevant fields and customizations. This feature takes the heavy lifting out of form creation, allowing users to focus on more strategic tasks while ensuring that the generated forms are optimized for engagement and data collection from the start.

Paperform’s AI capabilities extend beyond form creation, with features like question optimization and data analysis. The platform’s AI can suggest well-written and concise questions that encourage higher form completion rates.

Key Features:

Generates tailored forms based on user prompts.

Create personalized forms with no coding.

Question optimization and data analysis.

Suggests well-written and concise questions to achieve higher completion rates.

Visit Paperform →

Tally is reimagining the form-building landscape with its AI-powered platform, designed to eliminate complexity and streamline the creation process. This innovative tool stands out by focusing on simplicity and user experience, making professional form design accessible to everyone, regardless of technical background.

At the heart of Tally’s approach is its conversational AI interface. Rather than navigating complex menus, users can simply describe their form needs in natural language. The AI interprets these requests, instantly generating tailored forms complete with relevant fields and logic. This collaborative process feels more like working with a skilled assistant than operating software.

Tally’s commitment to privacy sets it apart in the AI form-building space. With European hosting, GDPR compliance, and end-to-end encryption, it offers a secure solution for handling sensitive data. This makes Tally particularly attractive for industries with strict data protection requirements, such as healthcare and finance.

Key Features:

Generates tailored forms based on user prompts, simplifying the form creation process.

Enables the creation of dynamic forms that adapt based on user inputs or external data.

Prioritizes data privacy and security, ensuring GDPR compliance, hosting in Europe, and encrypting form data both in transit and at rest.

Caters to a wide range of industries and use cases.

Easily integrate with popular tools like Notion, Slack, and Airtable, streamlining workflows and automating processes.

Visit Tally →

Wufoo has established itself as a trusted cloud-based form builder, serving over 3 million users including major brands like Amazon and Microsoft. Its interface simplifies the creation of various online forms, from registrations to payment forms, without requiring technical expertise. Wufoo’s strength lies in its user-friendly design, extensive template library, and robust reporting capabilities.

While not heavily AI-focused, Wufoo has recently integrated with include.ai, expanding its automation capabilities. This integration, combined with Wufoo’s existing features like automated database building and script generation, positions it as a powerful solution for efficient data collection and management. Wufoo’s ability to integrate with various third-party apps further enhances its appeal for businesses seeking to streamline their workflows.

Key Features:

Intuitive design for easy form creation and customization.

Visually appealing forms matching brand styles.

Automatic database, backend, and script building.

Connects with various third-party apps for streamlined workflows.

Over 3 million users and a decade of experience.

Visit Wufoo →

Forms.app distinguishes itself with its AI Form Generator, which allows users to create forms simply by describing their requirements in natural language. This innovative approach simplifies the form creation process, making it accessible to users of all technical levels. The platform’s AI capabilities extend to survey and quiz creation, offering specialized tools that quickly generate these types of forms with minimal user input.

The AI technology powering Forms.app continuously learns and improves, providing users with intelligent suggestions and optimizations to enhance form performance and user engagement. With integration capabilities spanning over 500 apps, Forms.app offers a flexible and efficient solution for businesses looking to streamline their data collection processes and form-based workflows.

Key Features:

Create custom forms by describing requirements to AI assistant.

Generate online surveys quickly with AI-powered survey maker.

Create engaging quizzes easily with AI assistance.

Expanding AI capabilities to meet evolving user needs.

Connects with over 500 apps for smooth workflow and data management.

Visit Forms.app →

Landingi combines landing page building with AI-powered form creation, offering a comprehensive solution for businesses aiming to generate leads and drive conversions. Its standout AI features include a text generator that creates compelling form content based on user prompts, and an SEO generator that optimizes forms for search engines. These tools significantly reduce the time and effort required for copywriting and SEO optimization.

Beyond content creation, Landingi’s AI capabilities extend to image processing and language support. An AI-powered background removal tool enhances the visual appeal of forms, while machine learning-powered translations enable the creation of multilingual forms. This combination of features makes Landingi a versatile platform for businesses looking to create high-converting forms and landing pages with a global reach.

Key Features:

Creates compelling form content based on user prompts.

AI-powered generator optimizes content for search engines.

AI tool for enhancing visual appeal of forms.

ML-powered tool for creating multilingual forms.

Combines AI-powered form creation with landing page building.

Visit Landingi →

MakeForms leverages AI to offer a secure and highly customizable form-building experience. Its AI-powered form builder automates the creation process by suggesting relevant questions and providing tailored templates based on user requirements. MakeForms sets itself apart with advanced AI capabilities like facial recognition for Know Your Customer (KYC) processes, ensuring enhanced security and identity verification.

The platform’s AI extends to form logic and data analysis. Conditional logic enables the creation of personalized forms that adapt based on respondents’ answers, while advanced data organization features like table, summary, and BI views allow for effective analysis and visualization of form data. This combination of security, customization, and analytics makes MakeForms a comprehensive solution for businesses requiring sophisticated form-building capabilities.

Key Features:

Suggests relevant questions and provides tailored templates.

Facial recognition for KYC enhances security and identity verification.

Conditional logic creates personalized forms adapting to respondents’ answers.

Data organization and analysis offers table, summary, and BI views for insights.

Includes secure payment collection, team collaboration, and integrations.

Visit MakeForms →

Why You Should Use an AI Form Generator

AI form generators are improving the way we create and manage online forms. These powerful tools leverage artificial intelligence to streamline form creation, making it easier than ever to design beautiful, interactive forms without extensive technical knowledge. By using an AI form builder, you can save time and resources while still creating user-friendly forms that effectively collect data.

One of the key advantages of AI-generated forms is their ability to adapt and improve based on user interactions. These intelligent systems can analyze form completion rates, identify potential roadblocks, and suggest optimizations to enhance the user experience. This means your forms can continuously evolve to become more effective at gathering the information you need, while also providing a smoother experience for your respondents.

Moreover, AI form generators often come with advanced features such as conditional logic, data analysis, and seamless integrations with other business tools. This allows you to create powerful forms that not only collect data but also help you derive meaningful insights from it. Whether you’re building a simple contact form or a complex survey, an AI form generator can help you create unique, engaging forms that stand out and deliver results. By embracing this technology, you’re not just keeping up with the latest trends – you’re positioning your organization at the forefront of efficient, intelligent data collection.

[infominescyber]

Affiliate Marketing and Proven Strategies: A Guide

affiliate marketing is, how it works, and successful strategies that could help you dominate this highly rewarding industry.

Affiliate Marketing and Proven Strategies: A Guide

Affiliate marketing has grown dramatically to become one of the biggest ways of generating money online for many individuals and organizations. If conducted properly, affiliate marketing can become a very rewarding business. Below, we outline what affiliate marketing is, how it works, and successful strategies that could help you dominate this highly rewarding industry.

What is Affiliate Marketing?

Affiliate marketing is a form of performance-based marketing where an individual, the affiliate, earns a commission for promoting a company's products or services. The affiliate gets paid when he or she sends a potential customer to the business's website using a special tracking link, and that visitor makes a purchase or takes a specific action.

There are usually three main players in affiliate marketing:

Merchant (or Advertiser): A business or brand which sells the product or services.

Affiliate (or Publisher): A person or a company who advertises the products and services of another merchant.

Customer: The person making the final purchase or completes a desired action.

The beauty of affiliate marketing is that it's performance-based. Affiliates only earn when the customer takes a specific action, for instance when purchasing a product, signing up for a newsletter, or clicking on an ad.

How Affiliate Marketing Works

The process of affiliate marketing is straightforwardly as follows:

Joining an Affiliate Program: Affiliates can join programs either from networks like Amazon Associates, ShareASale, or individual company affiliate programs.

Affiliate marketing: Acceptance leads the affiliate to promote either a product or service using his or her own unique affiliate link. This tracks the traffic driven to the merchant's website, and any subsequent sales are directly attributed to that affiliate.

Commission from sale: After a customer places an order, or performs an action, a commission is earned by that affiliate, who typically receives a percentage of that sale.

Payment: Based on the affiliate program's terms, the affiliates receive payment either monthly, bi-weekly, or other periodic schedules.

Affiliate Marketing Strategies

Affiliate marketing involves adopting the correct strategies that raise both traffic and conversion rates to achieve success in it. Here are some of the best strategies that you can use for maximum affiliate marketing success:

1. Choose the Right Niche

A right niche is one of the most critical steps in affiliate marketing. It determines your audience, the kind of products or services you will offer, and even the potential you have to make commissions. Think about these points when choosing a niche:

Passion and Expertise: Promote products or services you are passionate about or know well. You can then produce authentic content for your audience.

Profitability: Not all niches are equally profitable. For instance, niches like personal finance, health, and technology tend to have higher payouts.

Audience Demand: Ensure there is a demand for your chosen niche. Use tools like Google Trends or keyword research tools to gauge search interest.

By focusing on a niche that aligns with your interests and has high earning potential, you can ensure long-term success and engagement.

2. Focus on Content Marketing

Content is the main backbone of a successful affiliate marketing campaign. Unless and until content is engaging and valuable, attracting and converting the target prospects would be quite hard. Here are a few content strategies that will help:

Blogging: You post well-informative blog pieces that solve real problems for people in your audience. Examples might include product reviews, tutorials, or how-to documents. You also make sure the affiliate links appear there naturally.

Video Content: Videos are one of the best means to demonstrate a product and talk about its advantages. YouTube offers immense scope for affiliate marketers. Develop reviews, unboxing, or tutorials and link your affiliate link in the description of the video.

Email Marketing: Collect an email list and send them personal, valuable content. Use this content to promote related affiliate products by offering special offers or discounts.

Social Media: Instagram, TikTok, Facebook, and Pinterest are excellent places to use affiliate marketing. Share product recommendations, tutorials, and tips and use affiliate links in your bio, stories, or posts.https://cyberinfomines.com/blog-details/affiliate-marketing-and-proven-strategies:-a-guide

[erodeoffical002]

IDM TechPark In Erode

IDM TechPark: The Best Software Training Institute in Erode

In today’s competitive world, acquiring industry-relevant software skills is essential to build a successful career in technology. Whether you are a fresh graduate or a professional looking to upskill, choosing the right training institute is crucial. IDM TechPark in Erode stands out as one of the premier software training institutes, offering high-quality education and training that caters to the demands of the ever-evolving IT industry.

This comprehensive article dives into why IDM TechPark is the best choice for software training in Erode, exploring its courses, teaching methodology, facilities, placement assistance, and more.

1. About IDM TechPark

IDM TechPark has established itself as a leading institute for software training in Erode. With a mission to bridge the gap between academia and the IT industry, IDM TechPark offers a wide range of courses tailored to meet the needs of students, professionals, and businesses.

Key Highlights:

Industry-aligned curriculum

Experienced faculty with real-world expertise

State-of-the-art infrastructure

Strong emphasis on practical learning

The institute focuses on nurturing talent and providing students with the tools they need to succeed in their careers.

2. Courses Offered

IDM TechPark provides a diverse range of courses covering various domains in software development and IT. Here are some of the most sought-after programs:

a) Full-Stack Development

Front-end technologies: HTML, CSS, JavaScript, React, Angular

Back-end technologies: Node.js, Python, PHP, Java

Database management: MySQL, MongoDB

b) Data Science and Analytics

Python and R programming

Machine Learning and AI

Data visualization tools: Tableau, Power BI

Big Data technologies: Hadoop, Spark

c) Mobile App Development

Android development with Java/Kotlin

iOS development with Swift

Cross-platform frameworks: Flutter, React Native

d) Cloud Computing

Amazon Web Services (AWS)

Microsoft Azure

Google Cloud Platform

e) Cybersecurity

Ethical hacking

Network security

Penetration testing

f) Digital Marketing

SEO, SEM, and content marketing

Social media marketing

Email marketing and analytics

3. Teaching Methodology

IDM TechPark follows a holistic approach to teaching that combines theoretical knowledge with hands-on experience. Here’s what sets their methodology apart:

a) Project-Based Learning

Students work on real-world projects to apply the concepts they learn in class, ensuring a practical understanding of the subject matter.

b) Industry-Ready Curriculum

The courses are designed in collaboration with industry experts, keeping in mind the latest trends and technologies.

c) Interactive Sessions

The institute fosters an interactive learning environment where students can actively participate in discussions and problem-solving activities.

d) Access to Tools and Software

Students gain access to premium tools and software, enabling them to work with industry-standard resources.

4. Faculty

The faculty at IDM TechPark consists of experienced professionals who bring a wealth of knowledge and expertise to the classroom. They have:

Real-world experience in top IT companies

Expertise in various domains of software development and IT

A passion for teaching and mentoring students

5. Facilities and Infrastructure

IDM TechPark provides a conducive learning environment with state-of-the-art facilities:

a) Modern Classrooms

Equipped with advanced audio-visual aids to enhance the learning experience.

b) Fully Equipped Labs

Dedicated computer labs with high-speed internet and the latest software for hands-on training.

c) Library and Online Resources

Access to a vast collection of books, journals, and online materials to support learning.

d) Collaborative Spaces

Dedicated spaces for group discussions, brainstorming, and project collaborations.

6. Placement Assistance

One of the standout features of IDM TechPark is its robust placement support. The institute has a dedicated placement cell that ensures students are job-ready and connects them with top recruiters. Key aspects of their placement assistance include:

a) Resume Building and Interview Preparation

Personalized guidance to craft impressive resumes

Mock interviews and group discussions

b) Industry Connections

Strong ties with leading IT companies help students secure internships and job placements.

c) Job Alerts and Career Guidance

Regular updates about job openings and career counseling to help students make informed decisions.

Top recruiters for IDM TechPark graduates include Infosys, TCS, Wipro, Cognizant, and startups looking for skilled talent.

7. Success Stories

IDM TechPark has a proven track record of producing successful IT professionals. Many alumni have gone on to work for reputed companies, while others have launched their own startups. Testimonials from past students highlight the institute’s role in shaping their careers.

8. Who Should Join IDM TechPark?

IDM TechPark is ideal for:

Fresh Graduates: Looking to kickstart their careers in IT

Working Professionals: Seeking to upskill or switch to a different domain

Entrepreneurs: Wanting to build technical skills for their ventures

Students: Aspiring to gain practical knowledge and certifications

9. How to Enroll?

Enrolling at IDM TechPark is a simple process:

Visit the Institute: Attend a counseling session to understand the courses.

Choose a Program: Select a course based on your interests and career goals.

Complete Registration: Fill out the application form and pay the fees.

For more details, you can contact IDM TechPark directly via their website or phone.

10. Why Choose IDM TechPark?

Here’s why IDM TechPark stands out as the best software training institute in Erode:

Comprehensive and up-to-date curriculum

Focus on practical learning and industry readiness

Experienced faculty and state-of-the-art facilities

Strong placement support and success stories

Conclusion

In the fast-paced world of technology, staying ahead requires continuous learning and adaptation. IDM TechPark in Erode offers the perfect platform for aspiring IT professionals to gain the skills and knowledge they need to thrive in the industry. With its robust training programs, experienced faculty, and excellent placement support, IDM TechPark has rightfully earned its reputation as the best software training institute in Erode.

Whether you’re just starting your career or looking to upskill, IDM TechPark provides the resources, guidance, and opportunities to help you succeed. Enroll today and take the first step toward a rewarding career in the IT industry.

[techniktagebuch]

April 2023

Sechs Jahre Nichtstun, eine schöne Lösung für so viele Probleme

Vor fast genau sechs Jahren habe ich beschlossen, auch mal dieses Machine Learning auszuprobieren:

Gleich kann es losgehen, ich muss nur erst “Getting Started before your first lesson” lesen. Von dort schickt man mich weiter zum AWS deep learning setup video. Das Video ist 13 Minuten lang.

(Es folgen Probleme und Verwicklungen beim Setup, die Details kann man hier nachlesen.)

In Minute 12:45 sagt der Erzähler im Video: “Ok! It looks like everything is set up correctly and you’re ready to start using it.” Aber statt 12 Minuten und 45 Sekunden sind zwei Wochen vergangen, mein anfänglicher Enthusiasmus ist aufgebraucht und mein Interesse an Deep Learning erlahmt. Ich bin nicht einmal bis “Lesson 1” gekommen.

Im April 2023 sagt Aleks, dass er gerade einen sehr guten Onlinekurs über Machine Learning macht. Ich frage nach der Adresse, und sie kommt mir bekannt vor. Es ist derselbe Kurs!

“Das Setup war kein Problem?”, frage ich. Nein, sagt Aleks, Sache von ein paar Minuten.

Ich sehe mir "Practical Deep Learning for Coders 2022” an. Man braucht für den Kurs bestimmte Hardware. Generell benötigt Machine Learning Grafikprozessoren wegen der höheren Rechenleistung, und aus der Einleitung zum Kurs weiß ich jetzt, dass die aktuell verfügbaren Tools Nvidia-Grafikprozessoren voraussetzen*. Den Zugang zu dieser Hardware soll man mieten. Das war vor sechs Jahren auch schon so, nur dass das Mieten der Rechenleistung bei Amazon Web Services eine komplizierte und teure Sache war.

* Ich hatte an dieser Stelle schon “Grafikkarten” geschrieben, dann kam es mir aber wieder so vor, als müsste ich meinen Sprachgebrauch renovieren. In meiner Vorstellung handelt es sich um eine Steckkarte, ungefähr 10 x 20 cm groß, die in ein PC-Gehäuse eingebaut wird. So war das, als ich meine Computer noch in Einzelteilen kaufte, aber das ist zwanzig Jahre her. Deshalb habe ich mich für das unverbindliche Wort “Grafikprozessoren” entschieden. Aber wenn ich nach nvidia gpu machine learning suche, sehe ich sperrige Dinge, die nicht weit von meiner Erinnerung an Grafikkarten entfernt sind. Die große Rechenleistung braucht auch große Kühlleistung, deshalb sind zwei Lüfter auf der ... naja, Karte. Die Ergebnisse der Bildersuche sind etwas uneindeutig, aber es kommt mir so vor, als enthielte das Rechenzentrum, dessen Leistung ich gleich nutzen werde, wahrscheinlich große Gehäuse, in denen große Grafikkarten drin sind, vom Format her immer noch ungefähr wie vor zwanzig Jahren. Nur viel schneller.

2018 brauchte man AWS schon nicht mehr für den fast.ai-Onlinekurs. Stattdessen konnte man sich die Arbeitsumgebung bei Paperspace einrichten, einem anderen Cloud-Anbieter. Die Anleitung von 2018 klingt so, als hätte meine Geduld wahrscheinlich auch dafür nicht gereicht.

In der Version von 2019 hat der Kurs auf Google Colab gesetzt. Das heißt, dass man Jupyter Notebooks auf Google-Servern laufen lassen kann und keine eigene Python-Installation braucht, nur einen Browser. Colab gab es 2017 noch nicht, es wurde erst ein paar Monate nach meinem Scheitern, im Herbst 2017, für die Öffentlichkeit freigegeben. Allerdings klingt die Anleitung von 2019 immer noch kompliziert.

2020 wirkt es schon schaffbarer.

Auch die aktuelle Version des Kurses basiert auf Colab. Man muss sich dafür einen Account bei Kaggle einrichten. Soweit ich es bisher verstehe, dient dieser Kaggle-Zugang dazu, die Sache kostenlos zu machen. Colab würde ansonsten Geld kosten, weniger als ich 2017 bezahlt habe, aber eben Geld. Oder vielleicht liegen auch die Jupyter Notebooks mit den Kurs-Übungen bei Kaggle, keine Ahnung, man braucht es eben. (Update: In Kapitel 2 des Kurses merke ich, dass es noch mal anders ist, man hätte sich zwischen Colab und Kaggle entscheiden können. Zusammengefasst: Ich verstehe es nicht.)

Ich lege mir einen Kaggle-Account an und betrachte das erste Python-Notebook des Kurses. Es beginnt mit einem Test, der nur überprüft, ob man überhaupt Rechenleistung bei Kaggle in Anspruch nehmen darf. Das geht nämlich erst, wenn man eine Telefonnummer eingetragen und einen Verifikationscode eingetragen hat, der an diese Telefonnummer verschickt wird. Aber das Problem ist Teil des Kursablaufs und deshalb genau an der Stelle erklärt, an der es auftritt. Es kostet mich fünf Minuten, die vor allem im Warten auf die Zustellung der SMS mit dem Code bestehen.

Danach geht es immer noch nicht. Beim Versuch, die ersten Zeilen Code laufen zu lassen, bekomme ich eine Fehlermeldung, die mir sagt, dass ich das Internet einschalten soll:

“STOP: No internet. Click ‘>|’ in top right and set ‘Internet’ switch to on.”

Ich betrachte lange alles, was mit “top right” gemeint sein könnte, aber da ist kein solcher Schalter. Schließlich google ich die Fehlermeldung. Andere haben das Problem auch schon gehabt und gelöst. Der Schalter sieht weder so aus wie in der Fehlermeldung angedeutet, noch befindet er sich oben rechts. Man muss ein paar Menüs ein- und ein anderes ausklappen, dann wird er unten rechts sichtbar.

Ich bin also im Internet und muss erst das Internet einschalten, damit ich Dinge im Internet machen kann.

Aleks meint, wenn ich ihm gestern dabei zugehört hätte, wie er eine Viertelstunde lang laut fluchte, hätte ich schon gewusst, wie es geht. Hatte ich aber nicht.

Nach dem Einschalten des Internets kann ich das erste Jupyter-Notebook des Kurses betrachten und selbst ausprobieren, ob es wohl schwer ist, Frösche von Katzen zu unterscheiden. Für die Lösung aller Startprobleme von 2017 habe ich zwei Wochen gebraucht. 2023 noch eine Viertelstunde, und ich bin zuversichtlich, dass man um 2025 direkt in den Kurs einsteigen können wird.

(Kathrin Passig)

[skillzrevo]

Unlock Your Potential with Generative AI, Advanced AI, and Business Intelligence Courses

In a world driven by innovation, skills in Generative AI, Advanced AI, Data Science, and Business Intelligence are your ticket to a future-ready career. With the rapid adoption of AI technologies in India, the USA, and the Middle East, the time to invest in these high-demand fields is now. Whether you’re looking to advance your career, switch industries, or explore new opportunities, learning these skills opens the door to global job prospects and cutting-edge projects.

Why Focus on Generative AI and Advanced AI?

Generative AI has revolutionized industries by enabling machines to generate unique content, automate creative workflows, and develop intelligent tools. By enrolling in a Generative AI course, you’ll learn to work with groundbreaking tools like GPT-4, Stable Diffusion, and more, gaining expertise in creating AI-powered solutions.

On the other hand, an Advanced AI course equips you with technical mastery over machine learning, neural networks, and natural language processing (NLP). These skills are crucial for solving complex challenges and leading AI-powered transformations in any industry.

For those looking to dive deeper, a Master in Generative AI is the perfect way to specialize in this rapidly evolving domain and gain competitive leadership skills.

Global Job Market for AI Professionals

India

AI is transforming India’s economy, with the sector expected to create over 3.5 million AI-related jobs by 2030. From fintech and retail to healthcare and IT, companies like Tata Consultancy Services, Accenture, and Paytm are actively hiring AI specialists. Positions in Data Science, Business Intelligence, and AI start at ₹7 lakh per annum, with experienced professionals earning up to ₹30 lakh annually.

USA

The USA remains a pioneer in AI technology, with the AI market expected to grow at a CAGR of 36% over the next five years. Tech giants like Google, Amazon, and Meta are aggressively recruiting for roles such as Machine Learning Engineer, Generative AI Developer, and AI Architect, with salaries exceeding $150,000 per year. Reports indicate that Generative AI experts are among the top five most sought-after professionals in the USA.

Middle East

The Middle East is rapidly adopting AI to diversify its economies, especially in the UAE and Saudi Arabia. With a projected $15 billion AI market by 2030, industries like oil and gas, logistics, and real estate are leading the way in hiring Business Intelligence Analysts, AI Specialists, and Data Scientists. Starting salaries in the region range from $60,000 to $120,000 per year.

Learning Pathways to Success

Generative AI Courses: Learn how to design and implement AI systems that create text, images, videos, and more.

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These programs empower you to work on hands-on projects and gain practical knowledge that employers value.

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Generative AI in Marketing: AI tools like ChatGPT and DALL-E are transforming content creation, ad personalization, and brand engagement.

Advanced AI in Healthcare: Predictive models are helping doctors diagnose diseases early and deliver personalized treatments.

Business Intelligence in Finance: BI tools are optimizing risk analysis, fraud detection, and investment planning.

Data Science in E-commerce: Data-driven insights are shaping customer experiences and boosting sales strategies.

A LinkedIn report indicates that over 80% of global companies plan to expand their AI teams by 2025, signaling massive hiring opportunities.

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[teachercool]

What Are the Career Prospects for Data Scientists in Delhi?

paths across the globe. With its thriving tech ecosystem, Delhi is no exception. From startups to multinational corporations, organizations in Delhi are leveraging data science to drive business decisions, optimize processes, and stay competitive. If you are considering a career in Data scientist in Delhi, NCR offers a myriad of opportunities. Here’s an overview of what you can expect in this dynamic city.

1. Why Choose Data Science as a Career in Delhi?

Delhi is home to a diverse range of industries, including IT, e-commerce, healthcare, education, and finance. These sectors heavily rely on data-driven insights to grow and innovate. The demand for skilled data scientists is steadily increasing, and here’s why Delhi is a prime location:

Tech Hubs and Startups: Areas like Gurugram and Noida, part of the National Capital Region (NCR), host numerous IT parks and incubators for startups. These companies often require data scientists to analyze market trends and enhance customer experiences.

Access to Global Corporations: Delhi is a hub for multinational companies in finance, consulting, and IT services, offering opportunities to work on global projects.

Government Initiatives: The Indian government’s push for digital transformation and smart cities has created a demand for data scientists to work on public sector projects.

2. Skills in Demand for Data Scientists in Delhi

To excel as a data scientist in Delhi, you’ll need a combination of technical expertise and business acumen. Key skills include:

Programming Languages: Proficiency in Python, R, and SQL is essential.

Data Manipulation: Knowledge of tools like Pandas, NumPy, and Microsoft Excel.

Machine Learning: Familiarity with algorithms and libraries such as scikit-learn, TensorFlow, and PyTorch.

Data Visualization: Experience with tools like Tableau, Power BI, and Matplotlib.

Big Data Technologies: Skills in Hadoop, Spark, and cloud platforms like AWS or Azure are a plus.

Soft Skills: Strong problem-solving, communication, and storytelling abilities to present data insights effectively.

3. Top Employers Hiring Data Scientists in Delhi

Delhi’s job market for data scientists is vibrant, with opportunities across sectors. Some top employers include:

Tech Companies: HCL Technologies, Wipro, and TCS.

E-commerce Giants: Flipkart, Amazon India, and Zomato.

Financial Institutions: ICICI Bank, American Express, and Paytm.

Healthcare and Education: Fortis Healthcare and BYJU’S.

Consulting Firms: Deloitte, EY, and McKinsey & Company.

4. Salary Expectations

Data science is a lucrative field, and professionals in Delhi enjoy competitive salaries. According to recent industry reports:

Entry-Level: ₹5-8 LPA (Lakhs Per Annum)

Mid-Level: ₹10-20 LPA

Senior-Level: ₹20 LPA and above, with leadership roles offering even higher packages.

5. Educational and Networking Opportunities

Delhi offers excellent resources to kickstart or advance your career in data science:

Educational Institutions: Premier institutes like IIT Delhi, IIIT Delhi, and Delhi University offer specialized courses in data science and analytics.

Workshops and Meetups: Regular data science workshops, hackathons, and meetups in the city provide networking opportunities and hands-on experience.

Online Platforms: Platforms like Coursera, Udemy, and edX offer courses tailored for beginners and professionals.

6. Challenges to Consider

While Delhi’s data science market is promising, there are challenges to navigate:

Competition: The high demand attracts talent from across the country, making it a competitive field.

Continuous Learning: Data science evolves rapidly, requiring professionals to upskill regularly.

Cost of Living: While salaries are high, the cost of living in Delhi can offset some of the financial benefits.

7. Future of Data Science in Delhi

As businesses continue to embrace digital transformation, the future of data science in Delhi looks bright. Emerging technologies such as artificial intelligence (AI), natural language processing (NLP), and Internet of Things (IoT) will further fuel the demand for data science professionals.