Unknown Time Is Not Noon: Modeling Missing Temporal Data Without Inventing Facts
Missing data is not the same thing as a convenient default. That sounds obvious, yet temporal software regularly converts an empty time field into mid…
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Building auditable regulatory reference data: from legal text to versioned CSV
Building auditable regulatory reference data: from legal text to versioned CSV Regulatory information becomes hard to use the moment it is reduced to …
73,049 dates through a numerology rule: mostly mod 9, and 33's rarity depends on when you reduce
The usual headline is that 33 is the rarest Life Path, about half a percent. Half a percent of what, reduced in which order? Change the order, to anot…
Sequential Testing and the SPRT: How to Stop a Test Early Without Cheating
Sequential Testing and the SPRT: How to Stop a Test Early Without Cheating Meta description: Peeking at a fixed-sample A/B test inflates false positiv…
The Confidence Tier Model: How to Decide When Your Data Isn't Enough
The Confidence Tier Model: How to Decide When Your Data Isn't Enough Meta description: Most testing programs are built for traffic they don't have. Th…
Importance of Hypothesis Testing in Data Science
A hypothesis is a clear, testable statement about a population or process. Hypothesis testing then uses sample data to decide whether there is enough …
Building a Dice Roller That Teaches Probability: Batches, Histograms, and CSV
A dice roller looks like a one-line project: const value = Math . floor ( Math . random () * 6 ) + 1 ; That line is enough to draw a number from 1 thr…
Building JONAM: Using Copernicus Earth Observation Data to Help Restore Lake Victoria's Fisheries
"What if satellite data could help protect the livelihoods of millions who depend on Africa's largest lake?" Our team JONAM had the privilege of parti…
AI Data Lake and Lakehouse
The word "AI" appears in every data platform pitch now. Most of the time, it means nothing — a chatbot bolted onto a dashboard, an LLM that generates …
What Is a Semantic Layer? A Practical Guide for Data Engineers
Your data warehouse has a table called orders . It has columns like amount , status , created_at , and customer_id . Now three people ask "What was Q1…
How to Build Customer-Facing Analytics for B2B SaaS
Your B2B customers want to see their data. Usage metrics, billing summaries, conversion funnels, performance dashboards. Every customer expects analyt…
AI Reporting: How to Automate Reports Without Losing Trust
Your data team spends 40% of their time building reports. Weekly revenue summaries. Monthly board decks. Quarterly business reviews. Customer-facing u…
AI Data Analysis: Why Governed Metrics Beat Raw SQL Generation
AI data analysis tools are everywhere. Upload a spreadsheet to Julius AI and get a chart. Ask ChatGPT's Data Analyst to find trends. Connect Databrick…
Pandas vs Polars: Which One Should You Use in 2025?
Pandas vs Polars: Which One Should You Use in 2025? You’re probably still typing df.groupby() in Pandas while your Polars-using teammate has already f…
TOON: the JSON trick that cut my LLM prompt tokens by half
I run a small developer tools site, and the whole thing started with one annoyance: sending JSON arrays to GPT or Claude wastes a ridiculous amount of…
Protocol Buffers
Protocol Buffers are language-neutral, platform-neutral extensible mechanisms for serializing structured data. How it looks: (filed number + wiretype)…
Federation and the Lakehouse: Two Roads to Unified Data Access, and How to Know Which One to Take
Every data strategy document written this decade contains some version of the same sentence: we need a single place to access all our data. The senten…
7 Best WhatsApp APIs for Developers in 2026 (Compared)
Most developers reach for Twilio or Meta's official Cloud API the second WhatsApp comes up. That's usually the wrong first move. The official API want…
Your Data Pipeline Is Probably More Fragile Than You Think
Most engineering teams don't think much about their data pipelines until something breaks. That's partly because a healthy pipeline is almost invisibl…
PowerBi is smart but also lazy
Introduction For the past few days I have been doing data cleaning using PowerBi 34 columns to be precise.Data cleaning and transformation to me alway…
What does electricity have to do with knowledge graphs?
Christopher Nolan? Crime? Not really... But this is what my first tries for a knowledge graph did. It wasn't hallucinating. There was a real directed_…
How to Generate Dummy Data for Excel Spreadsheets Using FakerForge (Free CSV Export)
You've built a spreadsheet template. Maybe it's an inventory tracker, a customer list, or a sales report mockup. Now you need it to look real — filled…
We Counted the Skills in 360,000 Job Postings. AI Was the Most-Requested Hard Skill.
There's a lot of talk about AI reshaping hiring, so we checked it against our own data: 360,000+ job postings collected between December 27, 2025 and …
audiogear: как разметить миллионы аудиозаписей для TTS
Конвейер на Python + Hydra, который превращает папку с аудио в богато размеченный датасет: качество речи, просодия, разборчивость, спикер, транскрипци…
I Processed 500,000 Job Applications With AI. Here Is What the Data Actually Shows.
Full Transparency Disclaimer: I am the founder of Jobloo. After testing tools like LazyApply and Sonara and watching their browser extensions trigger …
How I Explored a US Health Dataset with Python — EDA + Hypothesis Testing
I recently completed an exploratory data analysis project on the NHANES (National Health and Nutrition Examination Survey) dataset from Kaggle. It's a…
I launched Beach Day API today
Today I launched Beach Day API , a developer API for real-time beach, ocean, water quality, advisory, amenity, access, and condition data. The goal is…
Apache Iceberg in Production: Compaction, Catalogs, and the Pitfalls Nobody Warns You About
Apache Iceberg looked like the answer to everything when we first adopted it. Open format, ACID transactions, time travel, schema evolution. We migrat…
Designing an Enterprise SFTP Integration Platform
Most engineering teams don't think about file transfer until an enterprise customer asks for it. Then suddenly it becomes a critical requirement. A fe…
Your model isn't underfitting. Your features are lazy.
Here's the scene I've watched play out on a dozen teams. Accuracy plateaus. Someone rips out the logistic regression, drops in XGBoost, and waits for …