How we helped a Real Estate Investment client in preparing Automated Data Governance reports

October 20, 2022

The Context

The client, a Real Estate Investment Management firm, wanted the TresVista team to automate the process of generation of monthly data governance reports and create a report based on dynamic criteria that can be updated as required.

The Objective

To develop a GUI-based tool, which reduces the effort for the client and allows them to make any changes seamlessly.

The Approach

The TresVista team followed the following process:

  • Data Gathering: Consolidated property details of real estate listings from different portals into a single table

  • Data Manipulation: Aggregated real estate listings in portfolios, locations, and other groups; and converted them to comparable data types

  • Data Governance Checks and Report Generation: Ran data governance checks based on values obtained for each listing or portfolio, based on dynamic criteria, and then generated the reports in the necessary format

The Challenges We Overcame

The major hurdles faced by the TresVista team were consolidating data from multiple sources; maintaining required confidentiality for different types of data, aggregating data based on various business logic, wherein data disparity was an issue and generating automated reports that the client can customize as per their evolving criteria for data governance checks.

The TresVista team overcame these hurdles by understanding the client’s IT infrastructure, using multiple technologies, applying business logic to make sense of data, and removing disparities wherever possible.

Final Product (Sanitized)

The Value Add – Catalyzing the Client’s Impact

The TresVista team created an automated report generation process that included reporting, detected issues in data, and implemented client formatting using a Graphic User Interface (GUI) equipped tool that the client could leverage for data governance checks for even new portals or newer parameters. This streamlined the entire end-to-end process of report generation whilst minimizing the chance of human error. The final process saves approximately a week’s worth of manual effort, every month.

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