๐ฅ ๐ฆ๐๐ผ๐ฝ ๐ช๐ฎ๐๐ฐ๐ต๐ถ๐ป๐ด ๐ง๐๐๐ผ๐ฟ๐ถ๐ฎ๐น๐.
๐ฆ๐๐ฎ๐ฟ๐ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ถ๐ป๐ด ๐๐ถ๐ธ๐ฒ ๐ฎ ๐ฅ๐ฒ๐ฎ๐น ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ.
If you want ๐ท๐ผ๐ฏ-๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐ฆ๐ค๐, ๐ฃ๐๐๐ต๐ผ๐ป, ๐ฃ๐๐ฆ๐ฝ๐ฎ๐ฟ๐ธ, ๐๐๐๐ฟ๐ฒ & ๐ฆ๐ป๐ผ๐๐ณ๐น๐ฎ๐ธ๐ฒ skills,
Hereโs where to practice and what exactly to practice because these are mainly expected in all the companies especially in EY, PwC, KPMG & Deloitte ๐
1๏ธโฃ ๐ฆ๐ค๐ โ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ฎ๐น & ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป-๐๐ฒ๐๐ฒ๐น
LeetCode (SQL): https://lnkd.in/gudFeUbZ
HackerRank (SQL): https://lnkd.in/g9hpE6vQ
SQLZoo: https://sqlzoo.net/
โข JOINs (INNER, LEFT, RIGHT)
โข GROUP BY & HAVING
โข Window functions (ROW_NUMBER, RANK)
โข CTEs (WITH clause)
โข Query optimization logic
2๏ธโฃ ๐ฃ๐๐๐ต๐ผ๐ป โ ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด ๐๐ผ๐ฐ๐๐
LeetCode (Python): https://lnkd.in/gaEvhsvi
HackerRank (Python): https://lnkd.in/gGHkAE47
Exercism (Python): https://lnkd.in/gAuvZmwZ
โข Functions & modules
โข File handling (CSV, JSON)
โข Data structures (list, dict)
โข Error handling & logging
โข Clean, readable code
3๏ธโฃ ๐ฃ๐๐ฆ๐ฝ๐ฎ๐ฟ๐ธ โ ๐๐ถ๐ด ๐๐ฎ๐๐ฎ ๐๐ฎ๐ป๐ฑ๐-๐ข๐ป
Databricks Community: https://lnkd.in/gpDTBDpq
SparkByExamples: https://lnkd.in/gfjnQ7Ud
Kaggle Notebooks: https://lnkd.in/gm7YU7Fp
โข DataFrames & transformations
โข Joins & aggregations
โข Partitioning & caching
โข Handling large datasets
โข Performance tuning basics
4๏ธโฃ ๐๐๐๐ฟ๐ฒ โ ๐๐ป๐ฑ-๐๐ผ-๐๐ป๐ฑ ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด
Azure Free Account: https://lnkd.in/gk_Dpb9v
Microsoft Learn: https://lnkd.in/gb8nTnBf
Azure Data Factory: https://lnkd.in/ggpsYk7X
โข Data ingestion using ADF
โข ADLS Gen2 storage layers
โข Parameterized pipelines
โข Incremental data loads
โข Monitoring & debugging
5๏ธโฃ ๐ฆ๐ป๐ผ๐๐ณ๐น๐ฎ๐ธ๐ฒ โ ๐ฅ๐ฒ๐ฎ๐น ๐๐ฎ๐๐ฎ ๐ช๐ฎ๐ฟ๐ฒ๐ต๐ผ๐๐๐ถ๐ป๐ด
Snowflake Trial: https://lnkd.in/g2dHRA9f
Sample Data: https://lnkd.in/grsV2X47
Snowflake Learn: https://lnkd.in/gVpiNKHF
โข Data Loading and Unloading
โข Fact & dimension modeling
โข ELT inside Snowflake
โข Query Profile analysis
โข Cost & performance tuning
๐ฆ๐๐ฎ๐ฟ๐ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ถ๐ป๐ด ๐๐ถ๐ธ๐ฒ ๐ฎ ๐ฅ๐ฒ๐ฎ๐น ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ.
If you want ๐ท๐ผ๐ฏ-๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐ฆ๐ค๐, ๐ฃ๐๐๐ต๐ผ๐ป, ๐ฃ๐๐ฆ๐ฝ๐ฎ๐ฟ๐ธ, ๐๐๐๐ฟ๐ฒ & ๐ฆ๐ป๐ผ๐๐ณ๐น๐ฎ๐ธ๐ฒ skills,
Hereโs where to practice and what exactly to practice because these are mainly expected in all the companies especially in EY, PwC, KPMG & Deloitte ๐
1๏ธโฃ ๐ฆ๐ค๐ โ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ฎ๐น & ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป-๐๐ฒ๐๐ฒ๐น
LeetCode (SQL): https://lnkd.in/gudFeUbZ
HackerRank (SQL): https://lnkd.in/g9hpE6vQ
SQLZoo: https://sqlzoo.net/
โข JOINs (INNER, LEFT, RIGHT)
โข GROUP BY & HAVING
โข Window functions (ROW_NUMBER, RANK)
โข CTEs (WITH clause)
โข Query optimization logic
2๏ธโฃ ๐ฃ๐๐๐ต๐ผ๐ป โ ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด ๐๐ผ๐ฐ๐๐
LeetCode (Python): https://lnkd.in/gaEvhsvi
HackerRank (Python): https://lnkd.in/gGHkAE47
Exercism (Python): https://lnkd.in/gAuvZmwZ
โข Functions & modules
โข File handling (CSV, JSON)
โข Data structures (list, dict)
โข Error handling & logging
โข Clean, readable code
3๏ธโฃ ๐ฃ๐๐ฆ๐ฝ๐ฎ๐ฟ๐ธ โ ๐๐ถ๐ด ๐๐ฎ๐๐ฎ ๐๐ฎ๐ป๐ฑ๐-๐ข๐ป
Databricks Community: https://lnkd.in/gpDTBDpq
SparkByExamples: https://lnkd.in/gfjnQ7Ud
Kaggle Notebooks: https://lnkd.in/gm7YU7Fp
โข DataFrames & transformations
โข Joins & aggregations
โข Partitioning & caching
โข Handling large datasets
โข Performance tuning basics
4๏ธโฃ ๐๐๐๐ฟ๐ฒ โ ๐๐ป๐ฑ-๐๐ผ-๐๐ป๐ฑ ๐๐ฎ๐๐ฎ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด
Azure Free Account: https://lnkd.in/gk_Dpb9v
Microsoft Learn: https://lnkd.in/gb8nTnBf
Azure Data Factory: https://lnkd.in/ggpsYk7X
โข Data ingestion using ADF
โข ADLS Gen2 storage layers
โข Parameterized pipelines
โข Incremental data loads
โข Monitoring & debugging
5๏ธโฃ ๐ฆ๐ป๐ผ๐๐ณ๐น๐ฎ๐ธ๐ฒ โ ๐ฅ๐ฒ๐ฎ๐น ๐๐ฎ๐๐ฎ ๐ช๐ฎ๐ฟ๐ฒ๐ต๐ผ๐๐๐ถ๐ป๐ด
Snowflake Trial: https://lnkd.in/g2dHRA9f
Sample Data: https://lnkd.in/grsV2X47
Snowflake Learn: https://lnkd.in/gVpiNKHF
โข Data Loading and Unloading
โข Fact & dimension modeling
โข ELT inside Snowflake
โข Query Profile analysis
โข Cost & performance tuning
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