#AWS Analytics

[astrowarr]

there's something about jimmy and martyn this season

four times over jimmy has walked the well-worn path into the realm of death all alone, his feet sinking in the inky, star-speckled puddles of the void and his hand shaking on the icy doorknob of After. and the familiarity— and oh, is it so familiar— never manages to suffocate the dread each and every time. the knowledge that this door, these wings, those eyes are all horrifyingly inevitable, following him, miraculously, across worlds.

until now. he steps in the pond of the void and there's a warm hand in his, so warm jimmy knows it to be unwelcome in this place. no one has ever been here with him before, and never in his endless lives and deaths has he ever been left staring wide-eyed at theback of someone's head, the back of martyn's head.

and martyn leads the way. there are no words— there never have been in this place— but his hand is firm and real in jimmy's. he walks confidently, the soles of his shoes marring the ground he walks across with ripples that never stop. and this time, martyn reaches out, and swings that haunting door wide open, ceasing its endless whispers all at once.

when martyn turns around, his eyes lock with jimmy's, and he doesn't speak— no one can, here, jimmy is sure of it— but he might as well, really. his eyes are tired, but they are certain. martyn says nothing, but jimmy hears him. of course he does.

follow me this time, would you?

[theboredvoid]

as a certified professional, I hate those AI girlfriend ads so much, NO "she" isn't real, no it isn't actually sentient, it's main objective is to get money off of you, how is it any different than renting a fancy sex doll you can't even touch? Stupid.

[no1ryomafan]

I never wanna weaponize the fact I’m a film student in an argument for simple reason 1. I don’t like getting into arguments anymore, shit sucks 2. It be really stupid of me, very “urm achtually” moment if I did but can I just say? Low key feels so weird to be in any conversation about adaptation discussions cause the argument are always “if they change everything from the original it’s bad” or “if it’s a movie/show/anime adaptation of a book/comic/manga and they take out anything at all it’s bad” because while there’s absolutely many cases of this especially recently unfortunately that do suck, I’ve been taught to like- not judge a adaptation for that? And even before then, I liked weird adaptations that definitely go off from the source material or leave out a lot when I’m the retro anime head, they do that shit a lot yet I feel the need to be like *hides I like anime Kikaider, casshern sins and all the getter ovas behind me* in a adaptation context cause I’d feel I’d be COOKED even if these are examples that actually do this shit correctly while being different.

[abathurofficial]

Abathur

At Abathur, we believe technology should empower, not complicate.

Our mission is to provide seamless, scalable, and secure solutions for businesses of all sizes. With a team of experts specializing in various tech domains, we ensure our clients stay ahead in an ever-evolving digital landscape.

Why Choose Us? Expert-Led Innovation – Our team is built on experience and expertise. Security First Approach – Cybersecurity is embedded in all our solutions. Scalable & Future-Proof – We design solutions that grow with you. Client-Centric Focus – Your success is our priority.

[marmaladesparrows]

one of the pieces ive been working on for ages is so very almost approaching done and i cannot wait to be free

i then won't be able to post it for who knows how long which sucks but we live

[ruvyn29]

I just need everyone to realize, that I don't understand anything

[pissfizz]

I know I’ve become an extremely unbearable person to be around and people don’t like me and that I am fundamentally awful. I know acknowledging what you’ve done or who you are us bad doesn’t make it okay and that you actually have to work to make things better. But I don’t know how. How do you make yourself a better person when it’s everything that you are that you’d have to get rid of. How am I supposed to fix myself without replacing every piece. How do I become something people like when I am at my core unpleasant and awful.

[inkykeiji]

No fr, I saw Hazbin fans on TT who ACTUALLY THOUGHT Alastor's last name was "Altruist". Like. They didn't comprehend it was a word he was mockingly attaching to his name after his performance in the finale.

oh my good god. once again i say, the media literacy (and possibly literacy, period) is buried beneath the ground like...that’s actually concerning. unless they were young teenagers who just didn’t know what the word meant,, tho idk if young teenagers should necessarily be watching hazbin but that’s a different conversation for a different time.

[geekonik26]

Open your career potential with Geekonik’s Online Best Data Analytics Course in Delhi NCR. Our industry-focused preparing covers Python, SQL, Exceed expectations, Control BI, and more, guided by master guides. Whether you're a fresher or proficient, pick up hands-on encounter, real-world ventures, and work help to flourish in the data-driven world. Select nowadays with Geekonik and gotten to be a certified Information Analytics master from the consolation of your home!

[cockworms]

just learned about a condition called cognitive disengagement syndrome (CDS) and holy shit. thats me. ive been feeling "too stupid to function" for a long time now and having feelings that maybe I am just stupid, maybe I didn't exercise my brain enough and it shrivelled like a fucking raisin or something and ive been hoping it's something that was actually out of my control the whole time so I don't have to feel guilty that I could have done something to prevent this

[bloggersmith]

Master Playwright Test Automation with Expert-Led Online Training

Master Playwright Test Automation with Expert-Led Online Training

[morganblogsblog]

How does AWS Data Analytics Services process and analyze large datasets efficiently?

AWS Data Analytics Services use a combination of tools and technologies to process large datasets efficiently:

Amazon S3 stores vast amounts of raw data securely.

AWS Glue automates data preparation and ETL (extract, transform, load) processes.

Amazon Redshift enables fast querying and data warehousing.

Amazon Kinesis handles real-time data streaming and analytics.

AWS Lambda allows serverless data processing without managing servers.

Conclusion:By integrating these services, AWS offers a flexible and scalable platform that accelerates data analysis workflows for large and complex datasets.

[proserpine-in-phases]

You know I used to try to leave like. Coherent comments on fics if I had strong feelings but lately I've just been like. "Oooooooughhh" or "damn" or similar. Please note that this is because I love the fic but am incapable of cogent analysis at this time

[onedatasoftwaresolutions]

How AWS Transforms Raw Data into Actionable Insights

Introduction

Businesses generate vast amounts of data daily, from customer interactions to product performance. However, without transforming this raw data into actionable insights, it’s difficult to make informed decisions. AWS Data Analytics offers a powerful suite of tools to simplify data collection, organization, and analysis. By leveraging AWS, companies can convert fragmented data into meaningful insights, driving smarter decisions and fostering business growth.

1. Data Collection and Integration

AWS makes it simple to collect data from various sources — whether from internal systems, cloud applications, or IoT devices. Services like AWS Glue and Amazon Kinesis help automate data collection, ensuring seamless integration of multiple data streams into a unified pipeline.

Data Sources AWS can pull data from internal systems (ERP, CRM, POS), websites, apps, IoT devices, and more.

Key Services

AWS Glue: Automates data discovery, cataloging, and preparation.

Amazon Kinesis: Captures real-time data streams for immediate analysis.

AWS Data Migration Services: Facilitates seamless migration of databases to the cloud.

By automating these processes, AWS ensures businesses have a unified, consistent view of their data.

2. Data Storage at Scale

AWS offers flexible, secure storage solutions to handle both structured and unstructured data. With services Amazon S3, Redshift, and RDS, businesses can scale storage without worrying about hardware costs.

Storage Options

Amazon S3: Ideal for storing large volumes of unstructured data.

Amazon Redshift: A data warehouse solution for quick analytics on structured data.

Amazon RDS & Aurora: Managed relational databases for handling transactional data.

AWS’s tiered storage options ensure businesses only pay for what they use, whether they need real-time analytics or long-term archiving.

3. Data Cleaning and Preparation

Raw data is often inconsistent and incomplete. AWS Data Analytics tools like AWS Glue DataBrew and AWS Lambda allow users to clean and format data without extensive coding, ensuring that your analytics processes work with high-quality data.

Data Wrangling Tools

AWS Glue DataBrew: A visual tool for easy data cleaning and transformation.

AWS Lambda: Run custom cleaning scripts in real-time.

By leveraging these tools, businesses can ensure that only accurate, trustworthy data is used for analysis.

4. Data Exploration and Analysis

Before diving into advanced modeling, it’s crucial to explore and understand the data. Amazon Athena and Amazon SageMaker Data Wrangler make it easy to run SQL queries, visualize datasets, and uncover trends and patterns in data.

Exploratory Tools

Amazon Athena: Query data directly from S3 using SQL.

Amazon Redshift Spectrum: Query S3 data alongside Redshift’s warehouse.

Amazon SageMaker Data Wrangler: Explore and visualize data features before modeling.

These tools help teams identify key trends and opportunities within their data, enabling more focused and efficient analysis.

5. Advanced Analytics & Machine Learning

AWS Data Analytics moves beyond traditional reporting by offering powerful AI/ML capabilities through services Amazon SageMaker and Amazon Forecast. These tools help businesses predict future outcomes, uncover anomalies, and gain actionable intelligence.

Key AI/ML Tools

Amazon SageMaker: An end-to-end platform for building and deploying machine learning models.

Amazon Forecast: Predicts business outcomes based on historical data.

Amazon Comprehend: Uses NLP to analyze and extract meaning from text data.

Amazon Lookout for Metrics: Detects anomalies in your data automatically.

These AI-driven services provide predictive and prescriptive insights, enabling proactive decision-making.

6. Visualization and Reporting

AWS’s Amazon QuickSight helps transform complex datasets into easily digestible dashboards and reports. With interactive charts and graphs, QuickSight allows businesses to visualize their data and make real-time decisions based on up-to-date information.

Powerful Visualization Tools

Amazon QuickSight: Creates customizable dashboards with interactive charts.

Integration with BI Tools: Easily integrates with third-party tools like Tableau and Power BI.

With these tools, stakeholders at all levels can easily interpret and act on data insights.

7. Data Security and Governance

AWS places a strong emphasis on data security with services AWS Identity and Access Management (IAM) and AWS Key Management Service (KMS). These tools provide robust encryption, access controls, and compliance features to ensure sensitive data remains protected while still being accessible for analysis.

Security Features

AWS IAM: Controls access to data based on user roles.

AWS KMS: Provides encryption for data both at rest and in transit.

Audit Tools: Services like AWS CloudTrail and AWS Config help track data usage and ensure compliance.

AWS also supports industry-specific data governance standards, making it suitable for regulated industries like finance and healthcare.

8. Real-World Example: Retail Company

Retailers are using AWS to combine data from physical stores, eCommerce platforms, and CRMs to optimize operations. By analyzing sales patterns, forecasting demand, and visualizing performance through AWS Data Analytics, they can make data-driven decisions that improve inventory management, marketing, and customer service.

For example, a retail chain might:

Use AWS Glue to integrate data from stores and eCommerce platforms.

Store data in S3 and query it using Athena.

Analyze sales data in Redshift to optimize product stocking.

Use SageMaker to forecast seasonal demand.

Visualize performance with QuickSight dashboards for daily decision-making.

This example illustrates how AWS Data Analytics turns raw data into actionable insights for improved business performance.

9. Why Choose AWS for Data Transformation?

AWS Data Analytics stands out due to its scalability, flexibility, and comprehensive service offering. Here’s what makes AWS the ideal choice:

Scalability: Grows with your business needs, from startups to large enterprises.

Cost-Efficiency: Pay only for the services you use, making it accessible for businesses of all sizes.

Automation: Reduces manual errors by automating data workflows.

Real-Time Insights: Provides near-instant data processing for quick decision-making.

Security: Offers enterprise-grade protection for sensitive data.

Global Reach: AWS’s infrastructure spans across regions, ensuring seamless access to data.

10. Getting Started with AWS Data Analytics

Partnering with a company, OneData, can help streamline the process of implementing AWS-powered data analytics solutions. With their expertise, businesses can quickly set up real-time dashboards, implement machine learning models, and get full support during the data transformation journey.

Conclusion

Raw data is everywhere, but actionable insights are rare. AWS bridges that gap by providing businesses with the tools to ingest, clean, analyze, and act on data at scale.

From real-time dashboards and forecasting to machine learning and anomaly detection, AWS enables you to see the full story your data is telling. With partners OneData, even complex data initiatives can be launched with ease.

Ready to transform your data into business intelligence? Start your journey with AWS today.

[nikhilvaidyahrc]

Top Certifications That Can Land You a Job in Tech

Published by Prism HRC – Leading IT Recruitment Agency in Mumbai

Breaking into the tech industry doesn’t always require a degree. With the rise of online learning and skill-based hiring, certifications have become the new ticket into some of the highest-paying and most in-demand jobs. Whether you're switching careers or upskilling to stay ahead, the right certification can boost your credibility and fast-track your job search.

Why Certifications Matter in Tech

Tech employers today are less focused on your college background and more interested in what you can actually do. Certifications show you're committed, skilled, and up-to-date with industry trends a huge plus in a fast-moving field like IT.

Let’s explore the top certifications in 2025 that are actually helping people land real tech jobs.

1. Google IT Support Professional Certificate

Perfect for: Beginners starting in tech or IT support This beginner-friendly course, offered through Coursera, teaches you everything from troubleshooting to networking. It’s backed by Google and respected across the industry.

Tip: It’s also a great way to pivot into other IT roles, including cybersecurity and network administration.

2. AWS Certified Solutions Architect – Associate

Perfect for: Cloud engineers, DevOps aspirants With cloud computing continuing to explode in 2025, AWS skills are hotter than ever. This cert proves you know how to design secure, scalable systems on the world’s most popular cloud platform.

Real Edge: Many employers prioritize candidates with AWS experience even over degree holders.

3. Microsoft Certified: Azure Fundamentals

Perfect for: Beginners interested in Microsoft cloud tools Azure is a close second to AWS in the cloud market. If you’re looking for a job at a company that uses Microsoft services, this foundational cert gives you a leg up.

4. CompTIA Security+

Perfect for: Cybersecurity beginners If you're aiming for a job in cybersecurity, this is often the first certification employers look for. It covers basic network security, risk management, and compliance.

Why it matters: As cyber threats grow, demand for cybersecurity professionals is rising rapidly.

5. Google Data Analytics Professional Certificate

Perfect for: Aspiring data analysts This course teaches data analysis, spreadsheets, SQL, Tableau, and more. It’s beginner-friendly and widely accepted by tech companies looking for entry-level analysts.

Industry Insight: Data skills are now essential across tech, not just for analysts, but for marketers, product managers, and more.

6. Certified ScrumMaster (CSM)

Perfect for: Project managers, product managers, team leads Tech teams often use Agile frameworks like Scrum. This certification helps you break into roles where communication, leadership, and sprint planning are key.

7. Cisco Certified Network Associate (CCNA)

Perfect for: Network engineers, IT support, and infrastructure roles If you’re into hardware, routers, switches, and network troubleshooting, this foundational cert is gold.

Why it helps: Many entry-level IT jobs prefer CCNA holders over generalists.

8. Meta (Facebook) Front-End Developer Certificate

Perfect for: Front-end developers and web designers This cert teaches HTML, CSS, React, and design systems. It’s hands-on and offered via Coursera in partnership with Meta.

The bonus? You also get portfolio projects to show in interviews.

How to Choose the Right Certification

Match it to your career goal – Don't do a cert just because it’s popular. Focus on the role you want.

Check job listings – Look at what certifications are frequently mentioned.

Time vs Value – Some certs take weeks, others months. Make sure the ROI is worth it.

- Based in Gorai-2, Borivali West, Mumbai - www.prismhrc.com - Instagram: @jobssimplified - LinkedIn: Prism HRC