Data Analytics & Business Intelligence

TL;DR Data analyst screening is unusually technical: the ATS matches specific languages...

Every data pipeline makes one foundational decision before a single line of code is written. Does it...

If you’re planning to start a career in data analytics, you’ve probably come across this question: Continue reading on Medium »

I use both professionally. They are not competing tools — they solve different problems. Here is the honest breakdown nobody gives you. Continue reading on Medi

One of the fastest ways to create inaccurate reports in Power BI is to combine fact tables that exist at different levels of detail… Continue reading on Power B

Every day, hospitals around the world have to generate petabytes of data from electronic health records (EHR) to patient check-in times… Continue reading on Med

To solve this problem, I built and published PuraLang Engine—an open-source, AI-driven Domain-Specific Language (DSL) framework that… Continue reading on Medium

Worksheets are the fundamental units for organizing and separating data in Excel files. A single...

In the winter of 1941, the codebreakers at Bletchley Park were not trying to read German messages directly. They were looking for patterns… Continue reading on

In the modern data-driven landscape, organizations generate vast amounts of information from disparate sources. Before this data can be… Continue reading on Med

Recently, I worked on an issue in Apache SeaTunnel where a job could sometimes stay in the CANCELING state forever after a user requested… Continue reading on M

Real-time analytics has become a core requirement for modern applications. Product teams expect...

Every Data Science Students program eventually hits the same wall. Somewhere around midterms, a problem set in statistical inference lands… Continue reading on

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Data Science Course: Build Future-Ready Skills for a Successful Career Continue reading on Medium »

As we conclude this 15-part series on Vyshyvanka, we want to leave you with practical tools. One of...

 Special month‑end discount available — enroll before the offer ends!  Institute of Data Science and Analytics, Janakpuri — trusted… Continue reading on Mediu

ClickHouse 26.6 Deep Dive: Streaming Queries, MPP Execution, Geospatial Analytics, and...

Finance wants to call it the new oil, but this is the oldest power source on Earth Continue reading on The Quantastic Journal »

arXiv:2606.26816v1 Announce Type: new Abstract: Heart Rate Variability (HRV) analysis is a key indicator of cardiac physiological state and aids in disease diag

Jun 26, 2026 · 1 min read Continue reading on Medium »

The 5 things worth building that automation can’t replace — and how you can start this week. Continue reading on Data Science Collective »

The 5 things worth building that automation can’t replace — and how you can start this week. Continue reading on Data Science Collective »

Text sorting can feel small until two databases give different answers for the same text. Reports can place uppercase names ahead of… Continue reading on Medium

What every beginner data analyst needs to understand before trusting any distribution plot. Continue reading on Medium »

What every beginner data analyst needs to understand before trusting any distribution plot. Continue reading on Medium »

In today’s data-driven business landscape, many companies invest in a CDP (Customer Data Platform) expecting better customer insights… Continue reading on Mediu

How Live-Service Telemetry Can Solve the Modern Isolation Epidemic Continue reading on Medium »

Most Pandas bottlenecks aren’t caused by large datasets — they’re caused by a handful of expensive coding patterns. Continue reading on Data Science Collective

Most Pandas bottlenecks aren’t caused by large datasets — they’re caused by a handful of expensive coding patterns. Continue reading on Data Science Collective

Most Pandas bottlenecks aren’t caused by large datasets — they’re caused by a handful of expensive coding patterns. Continue reading on Data Science Collective

Every SQL query you’ve ever written is secretly a chain of mathematical operations. Here’s the system hiding underneath it. Continue reading on Science Spectrum

The longer I worked on it, the less I cared about impressiveness and the more I cared about whether the system felt worth relying on. Continue reading on Medium

“Data is the new oil,” the quote says. But in reality, it may be far more valuable than oil, because oil is still measured in fiat… Continue reading on Medium »

Why the Grid Can't Keep Up, and Why that Drives Behind-The-Meter 50%+ of DCs/Year By 2028

As developers, data engineers, or analysts, we’ve all been there: you download a massive database...

Since the steam sale is live I wanted to post a Dev log on my personal project <a href="https:/

Wipro Centre of Excellence at Galgotias University Continue reading on Medium »

In today's data-driven world, organizations collect large amounts of data every day. However, raw...

Star schema vs snowflake schema comes down to one decision — whether you normalize your dimensions. Here's the difference, a worked example, and why the star us

A step-by-step investigation of customer experience using KPI decomposition, diagnostic analytics, and root cause thinking Continue reading on Code Like A Girl

Julius AI vs ChatGPT for Data Analysis: I Tested Both for a Month (2026) I've been burnt by "revolutionary" data tools before. So when I decided to pit Julius A

Today I started my Microsoft Fabric learning journey using the 60-day trial, and my first topic was...

Whether you should stick to a classic Ordinary Least Squares regression, introduce interaction terms, or pivot to a Tweedie distribution depends entirely on how

Sigma-Normalization: Why Order-Flow Signals Should Be Measured in Standard Deviations, Not...

As analytics tools have gotten more sophisticated, so has loss prevention teams’ understanding of the landscape and the strategies ORC groups favor.

Ask any Western fund manager what their best source is for Bombay Stock Exchange equities, Hong Kong...

A common barrier in data science projects is the perceived need for deep domain expertise before you can start building. Continue reading on Medium »