Analytics on alternative transaction-level data
Objective
A US-based boutique, pioneer in alternative data-driven research wanted to generate periodic and ad hoc reports using alternative data, and help evaluate the quality and suitability of data provided by alternative data vendors
Challenges
- Manually intensive process to generate ad hoc reports.
- Leveraging alternative data required significant remediation ahead of use.
Approach
- Analyzed new data to generate signals relevant to the telecom and media sectors.
- Automated data processing and optimized data pipelines to limit manual intervention.
- Analyzed additional external vendor data for quality and suitability for research purposes.
- Used Apache Spark, AWS Redshift, Tableau, and alternative data from external vendors in solution implementation.
Impact
- Automated processing of alternative data (credit and debit card transactions, POS data), trend analysis and generation of insights.
- Supported movement from legacy RDBMS to Apache Spark-based platform.
Questions