Datazip reposted this
𝐄𝐓𝐋 𝐨𝐫 𝐄𝐋𝐓: 𝐇𝐞𝐫𝐞'𝐬 𝐡𝐨𝐰 𝐭𝐨 𝐜𝐡𝐨𝐨𝐬𝐞. 🔍 ETL (Extract, Transform, Load) Imagine a strict code reviewer: "No raw data enters production without my approval." 𝙔𝙤𝙪 𝙘𝙡𝙚𝙖𝙣 𝙖𝙣𝙙 𝙥𝙧𝙚𝙥 𝙙𝙖𝙩𝙖 𝙗𝙚𝙛𝙤𝙧𝙚 𝙞𝙩 𝙡𝙖𝙣𝙙𝙨 𝙞𝙣 𝙮𝙤𝙪𝙧 𝙙𝙖𝙩𝙖𝙗𝙖𝙨𝙚. This method is used in the following cases: ✅ Sensitive data requiring immediate cleaning (PII, compliance) ✅ Legacy systems with limited processing power ✅ Complex business rules need applying pre-load ✅ Data quality must be enforced before storage 🔄 ELT (Extract, Load, Transform) Picture your data warehouse as an active GitHub repo: "Load it all in, tidy up with pull requests later." 𝙃𝙚𝙧𝙚, 𝙧𝙖𝙬 𝙙𝙖𝙩𝙖 𝙝𝙚𝙖𝙙𝙨 𝙨𝙩𝙧𝙖𝙞𝙜𝙝𝙩 𝙩𝙤 𝙨𝙩𝙤𝙧𝙖𝙜𝙚, 𝙩𝙧𝙖𝙣𝙨𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣𝙨 𝙝𝙖𝙥𝙥𝙚𝙣 𝙤𝙣 𝙙𝙚𝙢𝙖𝙣𝙙. It is: ✅ Suited for large-scale, rapid data ingestion. ✅ Great for cases where data transformations need flexibility. ✅ Ensures raw data access for various uses. ✅ Requires high compute capabilities in your data warehouse. The takeaway? 𝘗𝘳𝘰 𝘵𝘦𝘢𝘮𝘴 𝘰𝘧𝘵𝘦𝘯 𝘶𝘴𝘦 𝘣𝘰𝘵𝘩 𝘌𝘛𝘓 𝘢𝘯𝘥 𝘌𝘓𝘛, 𝘴𝘸𝘪𝘵𝘤𝘩𝘪𝘯𝘨 𝘮𝘦𝘵𝘩𝘰𝘥𝘴 𝘭𝘪𝘬𝘦 𝘧𝘶𝘭𝘭-𝘴𝘵𝘢𝘤𝘬 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘦𝘳𝘴. Which method do you prefer in your data strategy? Share in the comments below. ⤵️
