Problem Statement

The client faced significant operational challenges due to the absence of a centralized data warehouse. The fragmentation of data from various sources hindered their ability to establish a single source of truth, impeding efficient report generation and the extraction of actionable insights. This lack of consolidation affected decision-making processes and overall operational efficiency.

Approach & Solution

DataRopes.ai implemented an end-to-end ETL pipeline using Azure Data Factory to centralize data from multiple regions.

We integrated data from 6 SQL servers located across different regions, transferring the data to Azure Data Lake Storage for consolidation.
Followed Kimball's Star schema methodology to mirror over 50 tables from the source, ensuring efficient data structuring and easy access for reporting.
Built an automated pipeline that transferred over 500,000 rows of data daily, ensuring that the data warehouse remained up-to-date with real-time information.
Our team set up dynamic dashboards and ad-hoc reporting features, allowing the client to generate customized reports without manual intervention.

Results & Outcomes

The centralized data warehouse enabled the client to offer personalized dashboards to their end users, giving them clear insights into their own performance and allowing them to compare it against market trends. This enhanced client decision-making and strengthened their relationships with end users, leading to improved retention and new business opportunities. Ultimately, this contributed to a significant increase in ROI and long-term business growth.