Gathered requirements for designing lakehouse models that raise efficiency by 25%. Prepared data from Azure blob with PySpark in Databricks and connected to Tableau broke apart the dashboard with consumable chunks as multiple load time enhanced user experience. Used Table, aggregated and conditional calculations, advanced analytics.
Azure blob, Databricks, PySpark, Tableau Online
https://github.com/Sou-786/Financial-Complaint-Analysis-ETL/blob/main/Data%20Bricks%20Prep.pdf
