Trevor Dwyer·Sep 15Thirty Million Pounds of WrongHow a warehouse with the plan upside down taught me everything I know about data and why I’m rebuilding an AS/400 inside SQL Server thirty…A response icon2
InGoogle Cloud - CommunitybyTim Chapman·Sep 16Dude! Where’s my Clustered Index?!Heaps of fun ahead!A response icon2
InData Engineer ThingsbyVu Trinh·Sep 5Databricks introduced a new database that could change everything (?)LakebaseA response icon19
Trevor Dwyer·Sep 1Sum Over Every PathA spelling corrector in pure T-SQL, and what Feynman’s postulate had to do with itA response icon2
InData Engineer ThingsbyVu Trinh·Aug 318.2 minutes, and you will understand how most data systems execute joins.From Spark and Snowflake to BigQuery, here is how joins are builtA response icon3
Santanu Chandra·Sep 1510 Rare SQL Features Every Developer Should KnowYou already know JOIN and GROUP BY. These are the ones that turn 40 lines of application code into 4 lines of SQL.A response icon2
InJavarevisitedbyUmesh Kumar Yadav·May 6Google L5 level Interview: If You Join 10 Tables in an SQL Query, How Would You Optimize…During a recent technical interview at Goofle, a candidate was asked a challenging question:A response icon26
InTech with AbhishekbyAbhishek Kumar Gupta·Sep 850 dbt Interview Questions That Actually Separate Seniors From Everyone ElseI pulled these from real production incidents, GitHub issues, and the corners of the docs most engineers skim past — the questions that…A response icon3
Kashjalan·Sep 8A faster alternative to DuckDBDuckDB set the bar for querying Parquet on one machine. We put CtrlB next to it on ClickBench, same hardware, same file, same 43 queries…A response icon4
InCodeXbyAnton Martyniuk·Sep 810 Rare SQL Features Every Developer Should KnowMost developers use maybe 20 percent of SQL’s capabilities.A response icon2
Suhani Pareek·Just nowThe Test That Told the TruthA postmortem: the flaky test we learned to ignore, and the race condition it was trying to warn us about.
InTowards Data EngineeringbyLikith Raj Gollu·3h agoThe Visual Blueprint: The Data Modeling Fundamentals We Keep Coming Back ToThis post is a clean, visual refresher on how keys, joins, and redundancy shift across 3NF, Star, Snowflake, and OBT (One Big Table /…
Chizee·3h agoBillions of Log Rows, One Command to Make Them DisappearTelemetry and event logs only grow. Dump them into one giant table and every query — even one scoped to a single day — ends up scanning far…
Yerram venkata ramana reddy·3h ago10 SQL Practice Problems Every Data Analyst Should Be Able to SolveReading about JOINs and window functions only gets you so far. Here’s where you actually put them to work.
InTowards Data EngineeringbyLikith Raj Gollu·6h agoRethinking the Basics: What We Get Wrong About Normalization and Query SpeedMost data engineers assume they understand the trade-offs between normalization and denormalization — until execution speed and physical…
