Client is a leading insurance provider, having a vast amount of policy and insurance data stored in their existing data lake. They sought Sparity’s expertise to improve data quality, streamline reporting processes, and migrate existing reports to more efficient platforms.

ClientInsuranceServicesData scienceYear 2023

Key Challenges

  • Need for standardization of data in their data lake to facilitate efficient analysis and reporting across multiple dashboards.
  • Implementing ETL measures for all the key performance indicators (KPIs) to ensure accurate and consistent reporting.​
  • Recreation of existing reports to enhance data visualization capabilities and improve overall reporting efficiency


Google Cloud
Big Query


  • Sparity’s team conducted a thorough analysis of the client’s data lake to identify gaps and inconsistencies affecting the accuracy and reliability of reports and analytics.
  • Implemented data cleansing techniques to address deviations and duplications, ensuring improved data accuracy.
  • Collaborated with the client to understand their specific reporting needs, implemented ETL logics for all the key performance indicators (KPIs).
  • Loaded Google cloud storage data into BigQuery using scheduled queries and created consolidated aggregated tables for efficient analysis.
  • Developed a centralized reporting infrastructure using Looker Studio and Tableau. We migrated existing reports from spreadsheets to Google Sheets, seamlessly integrating with BigQuery for efficient data retrieval.


  • The data quality analysis and cleansing efforts resulted in improved data accuracy, reducing errors and inconsistencies in the client’s reports and analytics.
  • Met reporting requirements and provided tables to support multiple dashboards.
  • Migration of reports to Looker Studio and Tableau enabled the client to leverage advanced data visualization capabilities.