The 5 Vs of Big Data are volume, velocity, variety, veracity and value. This post walks a grocery chain through each one, so you can ask the same five questions about your own data before you choose a tool.
Data Lake vs Data Warehouse: What Each One Is For
Data Lake vs Data Warehouse is a choice between raw files and cleaned, modeled tables. This post compares schema on read with schema on write, who uses each, and why many teams combine them in a lakehouse.
ETL vs ELT: How Big Data Changed the Way We Load Data
ETL vs ELT comes down to when you transform: before the load on a separate engine, or after it inside the platform. This post compares the two and runs a small ELT pipeline in T-SQL on JSON orders.
Storing JSON in SQL Server
Storing JSON in SQL Server can use validated nvarchar or the native 2025 json type, with indexed paths and relational columns for stable facts.
Table Variables Survive ROLLBACK: Logging Errors in a Transaction
See how table variables survive rollback to retain error details, then write a permanent error log after a failed SQL Server transaction.
Trigram Matching: Finding Similar Words With an N-Gram Table
Build trigram matching with GENERATE_SERIES and an indexed n-gram table, rank shared pieces, and compare spelling similarity with SOUNDEX.
SQL SERVER – Select Columns from Stored Procedure Resultset
Need only some columns from a stored procedure resultset? Store it in a temp table with INSERT INTO and EXEC, then select what you need.