Analytics System

Challenges Faced

The existing analytics infrastructure presented significant hurdles:

• Performance Issues: Legacy system was extremely slow, making data exploration tedious.
• Data Silos: Information was fragmented across various databases and spreadsheets, preventing a holistic view.
• Lack of Timeliness: Reporting was manual and infrequent, hindering agile decision-making.
• Scalability Limits: The old system couldn't handle increasing data volumes or new data source integrations.

Solutions Implemented

We architected and delivered a modern, scalable analytics platform:

• Modern Data Pipeline: Built an ETL (Extract, Transform, Load) pipeline using AWS S3 for data lake storage, Apache Spark for processing, and Amazon Redshift as the data warehouse.
• Data Consolidation: Integrated disparate data sources (SQL databases, APIs, logs) into the centralized Redshift warehouse.
• Interactive Visualization: Developed dynamic and insightful dashboards using Tableau, connected directly to Redshift.
• Automation: Automated the entire data ingestion, processing, and reporting workflow.
• User Training: Empowered the client's team with training on leveraging the new Tableau dashboards.

Key Results

The revamped analytics system drove significant business value:

• Revenue Growth: Actionable insights directly contributed to a 25% increase in revenue.
• Timely Insights: Provided near real-time access to key performance indicators (KPIs).
• Efficiency Gains: Reduced time spent on manual reporting by over 70%.
• Scalability: Established a robust and scalable foundation capable of handling future data growth.

Key Technologies & Skills