#database tool

[knowledgehound]

In this digital world, companies rely on survey data to gather information about their targeted audience and their preferences. Businesses employ different methods to collect the survey data and analyze it. There are various mediums used to collect opinions and feedback from customers. While conducting a survey, researchers often choose multiple sources to collect data. KnowledgeHound shares the different methods used to collect the data.,,Learn more

[cuties-in-codices]

Where do you find these manuscripts? Is it like a website or do you find it randomly??

hey, thanks for the curiosity! lenghty answer below the cut :)

1)

medieval manuscripts are typically owned by libraries and showcased on the library's websites. so one thing i do is i randomly browse those digitized manuscript collections (like the collections of the bavarian state library or the bodleian libraries, to name just two), which everybody can do for free without any special access. some digital collections provide more useful tools than others (like search functions, filters, annotations on each manuscript). if they don't, the process of wading through numerous non-illustrated manuscripts before i find an illustrated one at all can be quite tedious.

2)

there are databases which help to navigate the vast sea of manuscripts. the one i couldn't live without personally use the most is called KdIH (Katalog der deutschsprachigen illustrierten Handschriften des Mittelalters). it's a project which aims to list all illustrated medieval manuscripts written in german dialects. the KdIH provides descriptions of the contents of each manuscript (with a focus on the illustrations), and if there's a digital reproduction of a manuscript available anywhere, the KdIH usually links to it. the KdIH is an invaluable tool for me because of its focus on illustrated manuscripts, because of the informations it provides for each manuscript, and because of its useful search function (once you've gotten over the initial confusion of how to navigate the website). the downside is that it includes only german manuscripts, which is one of the main reasons for the over-representation of german manuscripts on my blog (sorry about that).

3)

another important database for german manuscripts in general (i.e. not just illustrated ones) is the handschriftencensus, which catalogues information regarding the entirety of german language manuscripts of the middle ages, and also links to the digital reproductions of each manuscript.

4)

then there are simply considerable snowball effects. if you do even just superficial research on any medieval topic at all (say, if you open the wikipedia article on alchemy), you will inevitably stumble upon mentions of specific illustrated manuscripts. the next step is to simply search for a digital copy of the manuscript in question (this part can sometimes be easier said than done, especially when you're coming from wikipedia). one thing to keep in mind is that a manuscript illustration seldom comes alone - so every hint to any illustration at all is a greatly valuable one (if you do what i do lol). there's always gonna be something interesting in any given illustrated manuscript. (sidenote: one very effective 'cheat code' would be to simply go through all manuscripts that other online hobbyist archivers of manuscript illustrations have gone through before - like @discardingimages on tumblr - but some kind of 'professional pride' detains me from doing so. that's just a kind of stubbornness though. like, i want to find my material more or less on my own, not just the images but also the manuscripts, and i apply arbitrary rules to my search as to what exactly that means.)

5)

whatever tool or strategy i use to find specific illustrated manuscripts-- in the end, one unavoidable step is to actually manually skim through the (digitized) manuscript. i usually have at least a quick look at every single illustrated page, and i download or screenshot everything that is interesting to me. this process can take up to an hour per manuscript.

---

in conclusion, i'd say that finding cool illuminated manuscripts is much simpler than i would have thought before i started this blog. there are so many of them out there and they're basically just 'hidden in plain side', it's really astounding. finding the manuscripts doesn't require special skills, just some basic experience with/knowledge of the tools available. the reason i'm able to post interesting images almost daily is just that i spend a lot of time doing all of this, going through manuscripts, curating this blog, etc. i find a lot of comfort in it, i learn a lot along the way, and i immensely enjoy people's engagement with my posts. so that's that :)

[coquelicoq]

Qat lets you search for words matching a given pattern. It is the ideal tool for the discerning setter or solver of crosswords and other word puzzles. Try it now! A French-language version of Qat is also available, with the same search syntax. Essayez maintenant! Qat can find individual words matching simple and compound patterns (much like grep, Word Matcher and similar tools); beyond that, it also has an ‘equation solver’ mode that can find sets of words that simultaneously satisfy given constraints. Using this feature you can, for example, find pairs of words that are single-letter (or multiple-letter) misprints of one another, words that share common segments or that differ from one another in specified ways, words containing the same segments in different orders, and much more besides. See the examples below; a more formal explanation of the pattern syntax appears at the bottom of this page.

oh? my god???

[necro-hamster]

ppl defending ai art by completely ignoring the genuine major issues that people have with it and pretending like ppl r just mad because they're Art Elitists and think that art should only be made through Suffering instead of being easy are some of the most embarrassing ppl tumblr has been recommending to me lately

[smallerthanzer0]

(M:I Dead Reckoning spoilers)

OH

i briefly forgot that cyber crime exists and thought the movie was telling us that Benji straight up killed a man before joining the IMF

[coder23-data]

The Data Migration Odyssey: A Journey Across Platforms

As a database engineer, I thought I'd seen it all—until our company decided to migrate our entire database system to a new platform. What followed was an epic adventure filled with unexpected challenges, learning experiences, and a dash of heroism.

It all started on a typical Monday morning when my boss, the same stern woman with a flair for the dramatic, called me into her office. "Rookie," she began (despite my years of experience, the nickname had stuck), "we're moving to a new database platform. I need you to lead the migration."

I blinked. Migrating a database wasn't just about copying data from one place to another; it was like moving an entire city across the ocean. But I was ready for the challenge.

Phase 1: Planning the Expedition

First, I gathered my team and we started planning. We needed to understand the differences between the old and new systems, identify potential pitfalls, and develop a detailed migration strategy. It was like preparing for an expedition into uncharted territory.

We started by conducting a thorough audit of our existing database. This involved cataloging all tables, relationships, stored procedures, and triggers. We also reviewed performance metrics to identify any existing bottlenecks that could be addressed during the migration.

Phase 2: Mapping the Terrain

Next, we designed the new database design schema using schema builder online from dynobird. This was more than a simple translation; we took the opportunity to optimize our data structures and improve performance. It was like drafting a new map for our city, making sure every street and building was perfectly placed.

For example, our old database had a massive "orders" table that was a frequent source of slow queries. In the new schema, we split this table into more manageable segments, each optimized for specific types of queries.

Phase 3: The Great Migration

With our map in hand, it was time to start the migration. We wrote scripts to transfer data in batches, ensuring that we could monitor progress and handle any issues that arose. This step felt like loading up our ships and setting sail.

Of course, no epic journey is without its storms. We encountered data inconsistencies, unexpected compatibility issues, and performance hiccups. One particularly memorable moment was when we discovered a legacy system that had been quietly duplicating records for years. Fixing that felt like battling a sea monster, but we prevailed.

Phase 4: Settling the New Land

Once the data was successfully transferred, we focused on testing. We ran extensive queries, stress tests, and performance benchmarks to ensure everything was running smoothly. This was our version of exploring the new land and making sure it was fit for habitation.

We also trained our users on the new system, helping them adapt to the changes and take full advantage of the new features. Seeing their excitement and relief was like watching settlers build their new homes.

Phase 5: Celebrating the Journey

After weeks of hard work, the migration was complete. The new database was faster, more reliable, and easier to maintain. My boss, who had been closely following our progress, finally cracked a smile. "Excellent job, rookie," she said. "You've done it again."

To celebrate, she took the team out for a well-deserved dinner. As we clinked our glasses, I felt a deep sense of accomplishment. We had navigated a complex migration, overcome countless challenges, and emerged victorious.

Lessons Learned

Looking back, I realized that successful data migration requires careful planning, a deep understanding of both the old and new systems, and a willingness to tackle unexpected challenges head-on. It's a journey that tests your skills and resilience, but the rewards are well worth it.

So, if you ever find yourself leading a database migration, remember: plan meticulously, adapt to the challenges, and trust in your team's expertise. And don't forget to celebrate your successes along the way. You've earned it!

[latest-info]

How to Access Exclusive Research Archives Online

In the digital age, exclusive research archives have become invaluable resources for academics, professionals, and curious minds alike.

In the digital age, exclusive research archives have become invaluable resources for academics, professionals, and curious minds alike. These archives house a wealth of information, often containing rare and comprehensive collections that are not readily available to the general public. Accessing these archives can seem daunting, but with the right approach, it is entirely feasible. Here’s a…

[aceteling]

okay, what am i doing here

[im-a-freaking-joy]

I love that I do crossword puzzles often enough that if I say something completely random or that makes no sense, and I ask it like a question, my friends immediately respond with "how many letters" or "let me see" and then reach their hand out for my phone (which is where I do crosswords on)

They all know I'm not against asking for help but I don't like looking up the answers so they don't look anything up for me they just use their collective knowledge, and it is infinitely more fun that way for me lol.

Case and point- (this friend is planning on doing opera professionally in her future)

[networksupported]

sinking my head into my hands <- incorrect ai opinions blazed on dash

[knowledgehound]

Effective Data Insights — A Game Changer for Businesses

Data insights are crucial for businesses to make informed decisions and remain competitive in the ever-evolving market. With the increase in the volume, variety, and velocity of data, it has become necessary for organizations to have the capability to analyze data and derive insights that help them make data-driven decisions. This article will explore the importance of data insights for businesses, steps to achieving effective data insights, best practices, tools, challenges, and future of data insights.

Introduction to Data Insights

According to KnowledgeHound, Data insights refer to the process of analyzing and interpreting data to extract meaningful information that can be used to make informed decisions.

It involves using various tools and techniques to identify patterns, trends, and relationships in data. There are many resources available for beginners who want to learn about data analytics, including online courses and guides.

These resources cover topics such as the role of a data analyst, tools used in data analysis, and the entire data analysis process. With the increasing demand for professionals with skills in data analytics, learning this field can be a great way to kickstart a career.

Importance of Data Insights for Businesses

Data insights are crucial for businesses as they provide valuable information that can be used to make informed decisions. By analyzing customer data from various channels, businesses can gain insights into customer behavior and preferences, which can help them provide a more personalized experience.

Historical data analysis can also help businesses anticipate fluctuations in consumer demand and make better business decisions. Companies that embrace data analytics initiatives can experience significant financial returns. Data analytics helps businesses optimize their performance by identifying areas for improvement and making strategic investments.

Implementing data analytics into the business model means companies can stay competitive in today’s market by making informed decisions based on real-time data.

Steps to Achieving Effective Data Insights

Achieving effective data insights involves several steps.

Firstly, it is important to align the data strategy with the business strategy and identify relevant business drivers that could be positively impacted by data and analytics.

Secondly, organizations need to implement processes such as data cataloging and governance and embrace culture changes to achieve effective analytics programs.

Thirdly, businesses should use deep learning to get value from unstructured data.

Finally, carrying out various analyses on the data is essential to obtain insights. The four types of data analysis include descriptive, diagnostic, predictive, and prescriptive analysis.

By following these steps, businesses can turn their data into actionable insights that can be used to make informed decisions.

Best Practices for Data Insights

To achieve the best results from data insights, businesses should follow some best practices.

It is important to define business objectives and identify the key performance indicators that will be used to measure success.

Building high-performance analytics teams and promoting data literacy within the organization can help ensure that everyone understands how to use data effectively.

Collecting, storing, and organizing data correctly is essential for accurate analysis.

Segmenting the audience can help businesses gain a better understanding of their customers’ behavior and preferences.

Using data storytelling can help promote insights by making complex data more accessible and understandable.

Utilizing new infrastructure technology and more advanced analytics can help businesses stay ahead of the competition.

By following these best practices, businesses can turn their data into actionable insights that drive growth and success.

Tools for Data Insights

There are many tools available for data insights that businesses can use to analyze and interpret their data. Some of the most widely used business analytics tools include Microsoft Power BI, Tableau, Qlik Sense, Excel and KnowledgeHound.

These tools are designed to help businesses visualize and analyze their data to gain insights into customer behavior, market trends, and other key metrics. These tools offer a range of features such as data visualization, predictive modeling, machine learning algorithms, and more.

By using these tools effectively, businesses can turn their data into actionable insights that drive growth and success.

Challenges in Data Insights

There are several challenges that businesses face when it comes to data insights.

Managing vast amounts of data can be a challenge, as it requires the right tools and techniques to analyze and interpret the data effectively.

Seelecting the right analytics tool can be difficult, as there are many options available and each has its own strengths and weaknesses.

Data visualization can be challenging, as it requires businesses to present complex data in a way that is easy to understand.

Dealing with data from multiple sources can be a challenge, as it requires businesses to integrate different types of data into a single system.

Low-quality data can also pose a challenge, as it can lead to inaccurate insights and decisions.

Other challenges include cultural dynamics within the organization, inaccessible data, lack of system integration, excessive costs, complexity and skills gaps.

By addressing these challenges effectively through proper planning and implementation of best practices for data insights, businesses can turn their data into actionable insights that drive growth and success.

Future of Data Insights

The future of data insights is promising, with several trends emerging that are expected to shape the industry in the coming years.

Businesses are expected to emphasize business intelligence, edge data, and cloud-native technologies.

Data democratization, artificial intelligence, and real-time data analytics are expected to become more prevalent.

Adaptive AI systems and metadata-driven data fabric are also expected to gain traction.

Real-time automated decision making and no-code solutions are also predicted to be important trends in the future of data insights.

Data quality and observability will continue to be important factors in ensuring accurate insights from data analysis.

By staying up-to-date with these trends and adopting new technologies and techniques as they emerge, businesses can stay ahead of the competition and turn their data into actionable insights that drive growth and success.

Also Read: Different Types of Survey Data Collection Methods You Should Know

[fiendfriend]

Love making big compilations of links to web pages and pdfs

Need to get back to coding my stupid little website so that I might compile all of my compilations

[vaultsixtynine]

happy moon landing day AND happy day i finally get my prototype tool out of dev finally.

[ritualvirtuality]

soooo i just finished cataloging all of our books (at least i think so) so here's a chart and some superlatives!

some explanations on the above chart: we use a tagging system for topics, so one book can be in multiple topics (and as a result multiple supertopics). yes, the supertopics are a little strange, but we chose them to best fit our library so that books would be generally well distributed between them. also i really wish i could figure out how to change where the labels are pointing but unfortunately idk google sheets charts that well...

and thats some superlatives for our library. the dates are original publication dates (for the case of Medea, its the publication of that specific translation).

more of this may be coming! if im interested in doing it lol

[skylordhorus]

i kinda fail to see how ai art in its current inception and majority utilisation is a 'tool' like. a fill bucket is a tool. fx brushes and filters and magic wand selection and line stabilisation are tools. how is plugging prompts into a machine fed on existing works and getting finished-looking pieces a 'tool'

[jcmarchi]

Dhiren Bhatia, Co-Founder & CEO of Inventive AI – Interiew Series

New Post has been published on https://thedigitalinsider.com/dhiren-bhatia-co-founder-ceo-of-inventive-ai-interiew-series/

Dhiren Bhatia, Co-Founder & CEO of Inventive AI – Interiew Series

Dhiren Bhatia is the Co-Founder & CEO of Inventive AI,  an AI-powered RFP and questionnaire response management platform.

RFP stands for Request for Proposal, a formal document issued by organizations to invite vendors or service providers to submit proposals for specific projects or services. The RFP outlines the project requirements, objectives, and evaluation criteria, allowing qualified vendors to submit detailed bids on how they plan to meet the organization’s needs.

Inventive AI is an AI-powered platform designed to streamline and optimize the response process for RFPs and questionnaires. By automating tasks such as drafting responses, gathering relevant data, and customizing proposals for specific clients, Inventive AI significantly improves the efficiency of sales response workflows, driving over 70% efficiency gains for businesses. This allows companies to respond to RFPs faster, more accurately, and with greater consistency, ultimately enhancing their chances of winning more contracts.

What inspired the founding of Inventive AI, and how did your personal experiences with RFP workflows shape its mission?

After taking some time off following my last exit (selling Viewics to Roche), I realized I missed the excitement and challenges of building a startup. During my time at Roche, my teams were involved in numerous RFPs, and I consistently saw how difficult it was to craft strategic, efficient responses. This experience highlighted a clear opportunity, and I set out to explore it further. Through conversations and interviews with dozens of companies, I validated that this pain point was widespread, reinforcing my decision to dive back in and build a solution to address it.

What were the key pain points in the RFP process that you identified, and how does Inventive AI address those challenges?

The key pain points in the RFP process include:

Manual, time-consuming effort: The process can take days or even weeks of work due to the extensive manual input required.

Managing content and knowledge: It’s challenging to maintain and organize the knowledge base for crafting accurate and relevant responses.

Strategic responses: Responding effectively requires understanding the customer’s specific needs and considering the competition, making it difficult to tailor responses strategically.

Collaboration across teams: Gathering input from multiple subject matter experts and senior stakeholders can be cumbersome and lead to delays.

Compliance and risk management: Ensuring alignment with regulatory requirements, internal policies, and legal constraints adds complexity and potential risks.

Inventive AI addresses these challenges with a suite of proprietary AI-driven agents designed to automate and streamline key aspects of the process. By leveraging AI, the platform significantly reduces manual effort, organizes and optimizes content management, enhances strategic response generation, simplifies stakeholder collaboration, and ensures compliance and risk management—all in one integrated solution.

How does Inventive AI’s technology make RFP responses faster and more accurate compared to traditional methods?

Our founding team brings deep expertise in machine learning, particularly in language models. Gaurav Nemade, an early Product Manager at Google Brain, contributed to the development of LLMs, while Vishakh Hegde conducted AI research at Stanford University. Leveraging this expertise, we’ve developed a proprietary pipeline and suite of tools that deliver accurate, strategic responses within seconds, all grounded in our customers’ unique knowledge sources. This enables us to provide a solution that is not only fast but also highly tailored to each client’s needs.

What makes RFP management a critical area for automation, and how does Inventive AI tackle this?

RFP management is a critical area for automation because an RFP signifies a high level of interest and buying intent for a company’s products or services. Delivering a high-quality, strategic response is crucial for maximizing sales opportunities. This process demands accuracy, compliance, risk management, and competitive positioning, all of which can be time-consuming and prone to errors when done manually.

Inventive AI tackles this challenge by automating key aspects of RFP management through advanced AI technology. The platform ensures that responses are accurate, compliant with regulations, and strategically aligned with customer needs. By automating these tasks, Inventive AI not only improves the quality and consistency of responses but also allows companies to handle a higher volume of RFPs, expanding their ability to pursue more opportunities and ultimately increasing win rates.

Why are RFPs often overlooked in digital transformation, and how is Inventive AI changing this dynamic?

RFPs are often overlooked in digital transformation initiatives because they are seen as administrative or transactional tasks rather than strategic opportunities for innovation. Many companies focus their digital transformation efforts on customer-facing functions, internal operations, or product development, leaving procurement and sales processes, like RFP management, relatively untouched. This is partly because RFP processes are traditionally manual and highly customized, which can make them seem less suitable for automation or digital overhaul.

Additionally, the complexity and cross-functional nature of RFPs often lead companies to assume that automating or streamlining these processes would be too difficult or disruptive. As a result, the potential gains from improving RFP workflows—such as increased efficiency, better accuracy, faster turnaround times, and enhanced competitiveness—are frequently missed during digital transformation efforts. However, with the progress in AI and thereby solutions like Inventive AI, automating RFP management is not only feasible but can also provide significant strategic advantages.

Can you explain how the unified knowledge hub works, and how it integrates with various enterprise systems?

The Inventive AI Knowledge Hub functions as a centralized, AI-powered resource that acts like a subject matter expert (SME) with access to a company’s vast, distributed knowledge. In a typical enterprise, relevant content for responding to sales questionnaires and RFPs exists across multiple systems and departments, making it difficult to manually pull together accurate and strategic responses. A simple Q&A library of boilerplate responses is often insufficient for creating competitive, tailored proposals.

Inventive AI addresses this challenge by integrating with commonly used enterprise systems such as Salesforce, Hubspot, Seismic, Google Drive, SharePoint, OneDrive, and more. Our AI can automatically ingest and understand the context of the incoming RFP, retrieving the most relevant information from across these platforms to craft high-quality responses. Additionally, our AI agents—responsible for tasks such as competitive research, error checking, conflict resolution, and compliance and risk management—operate on this unified Knowledge Hub, ensuring consistency and accuracy by leveraging a complete, connected view of the company’s knowledge, rather than relying on siloed content.

What are the key features of Inventive AI that differentiate it from other RFP management tools on the market?

What differentiates Inventive AI from other RFP management tools is our focus on helping customers win RFPs, not just answer questions. While many tools simply provide a way to search for boilerplate responses within a static database, requiring the customer to constantly maintain and update it, Inventive AI goes far beyond that. Our platform dynamically leverages enterprise-wide knowledge and uses advanced AI to generate strategic, high-quality responses tailored to each RFP, significantly increasing win rates.

Our deep enterprise experience and AI expertise allow us to address both the business and technical aspects of the RFP process. We’ve built a system that not only delivers accurate responses but also effectively manages AI challenges like language model hallucinations, ensuring precision and relevance in every response. This level of response quality and strategic insight is unmatched in the market, making Inventive AI a true competitive advantage for RFP management.

How does the AI Content Manager ensure that only the most relevant and up-to-date information is used in RFP responses?

This is a great question and easier said than done. While it’s relatively straightforward to create a compelling demo using popular AI tools like OpenAI, Google, or AWS, our platform goes beyond simple solutions that are just not good enough for enterprise settings. Drawing from our AI research backgrounds at Google and Stanford Research, we’ve built a proprietary machine learning pipeline combined with a strategy of specialized AI agents. This allows us to ensure that only the most relevant and up-to-date content is used in RFP responses, continuously refining the accuracy of the information.

When the AI encounters uncertainty, it doesn’t make assumptions. Instead, it presents users with potential options and learns from the feedback provided. This iterative learning ensures that future responses are even more precise when similar questions arise, improving over time and ensuring that RFP responses stay relevant, current, and strategic.

What kind of productivity boosts have users seen by using Inventive AI’s suite of AI agents, and what specific tasks do these agents handle?

Users of Inventive AI’s suite of AI agents have seen significant productivity boosts, particularly in their ability to respond to a greater number of RFPs, which directly impacts top-line revenue. By generating more strategic, accurate, and tailored responses, companies have also experienced higher win rates. Customers report that they complete the RFP process 70% faster than before, allowing them to take on more opportunities without sacrificing quality.

Our AI agents handle a variety of critical tasks, such as conducting competitive analysis, brainstorming response ideas, and detecting stale or outdated content. They also identify conflicting information within responses, unearth multiple potential answers to RFP questions, and check for compliance with regulatory or internal guidelines. These automated capabilities enable teams to focus on higher-value activities, ensuring that responses are both efficient and strategically sound.

Thank you for the great interview, readers who wish to learn more should visit Inventive AI.