Description: In this exercise, I performed data transformation via Python Pandas and MySQL Server to onboard new client data which was received in the format of the client’s legacy database. The appropriate import templates were selected after careful consideration of client needs and data availability.
The case study company is a comprehensive wealth management product suite, in which the data aggregation step enables a flexible internal data ownership structure allowing dynamic financial reporting on all 3 levels (client, household, & account). I attempted to mimic the tech stack that the company uses which is why I performed my data transformations via Python Pandas and MySQL server.
TIME TO COMPLETE: 72 HOURS
Note: Please read the executive summary file for an in-depth coverage of the methods used to transform the client's legacy data into the new format.
This repo contains the case study instructions, the code written to produce the desired output, an executive summary, and the client files (including the mappings to the new format)
The results are in the "EXPORT_BIN" folder and were designed to match the import templates given in the "ImportTemplates" folder. The type mappings between the legacy system and the new system are in the "ReferenceFiles" folder.
- Name: Eshaan Vora
- Email: EshaanVora@gmail.com
- Case Study: Data Solutions Consultant
- CaseStudy.py
- ExecutiveSummary.docx
- /EXPORT_BIN
- /FilesReceived_LegacyData
- /ImportTemplates
- Instructions.pdf
- /ReferenceFiles
- README.md
- None
- Modify database connection credentials to your local or server connection
- Run: python3 CaseStudy.py