Techtter

If you want to become good at Data Engineering, then learn these use cases:


1. 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐃𝐚𝐭𝐚 𝐋𝐚𝐤𝐞 𝐯𝐬. 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞
🔗lnkd.in/gEpmTyMS

2. 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐌𝐞𝐭𝐚𝐝𝐚𝐭𝐚-𝐃𝐫𝐢𝐯𝐞𝐧 𝐄𝐓𝐋 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬
🔗 lnkd.in/g2W5t3iq

3. 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐢𝐧𝐠 𝐌𝐞𝐝𝐚𝐥𝐥𝐢𝐨𝐧 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐢𝐧 𝐃𝐚𝐭𝐚𝐛𝐫𝐢𝐜𝐤𝐬
🔗lnkd.in/gXvicgyt

4. 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐃𝐚𝐭𝐚 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐰𝐢𝐭𝐡 𝐀𝐢𝐫𝐟𝐥𝐨𝐰
🔗lnkd.in/gynhyDTP

5. 𝐃𝐞𝐥𝐭𝐚 𝐋𝐚𝐤𝐞: 𝐀𝐂𝐈𝐃 𝐓𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐢𝐧 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚
🔗 lnkd.in/gRk4wmXR

6. 𝐑𝐞𝐚𝐥-𝐓𝐢𝐦𝐞 𝐒𝐭𝐫𝐞𝐚𝐦𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐏𝐲𝐒𝐩𝐚𝐫𝐤
🔗lnkd.in/gHj2pF2V

7. 𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐂𝐡𝐞𝐜𝐤𝐬 𝐢𝐧 𝐄𝐓𝐋 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬
🔗lnkd.in/g7jnf-Zk

8. 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐓𝐮𝐧𝐢𝐧𝐠 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬 𝐢𝐧 𝐒𝐩𝐚𝐫𝐤
🔗lnkd.in/gn2rFNXC

9. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐝𝐚𝐭𝐚 𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 𝐢𝐧 𝐒𝐐𝐋
🔗 lnkd.in/gjrQSEWM

10. 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 𝐟𝐨𝐫 𝐀𝐳𝐮𝐫𝐞 𝐃𝐚𝐭𝐚 𝐅𝐚𝐜𝐭𝐨𝐫𝐲
🔗 lnkd.in/gragXs6E

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