Tshegofatso Molobe

Optimised an ingest master application using Python that automated data ingestion, data staging, schema comparison, and hive table creation for relational data, reducing manual input by 60% and improving accuracy by 80%. Conducted detailed analysis of Hive performance with Snappy and GZIP compression methods, resulting in a 50% improved data processing efficiency. Supported AWS migration efforts by researching Hive platform usage through YARN and HDFS logs, contributing to a more informed migration strategy. Evaluated workflow performance by analysing container resource usage, leading to a 40% increase in system efficiency.

Successfully deployed and optimised a Power BI model using SQL to detect financial advisors making policy alterations, improving early detection of suspicious activities. Enhanced the model to identify multiple alterations on the same policy and cross-intermediary modifications, boosting fraud prevention efforts. Orchestrated the sourcing, analysis, and integration of client, policy, financial history, and retention data to identify key factors driving successful client retention. Facilitated cross-departmental collaboration and streamlined communication by translating complex data concepts for non-technical stakeholders. Developed and optimised over 15 SQL scripts for ad hoc reporting, improving data retrieval speed and reducing report generation time.