Created data lake to enable single version of truth across the organization and drive analytics and reporting for the entire organization.


The data for a client was spread across different systems with no single custodian for different data sets. As a result, any analysis was time consuming. In many cases, same metrics reported by different parts of the organization contradicted with each other and lot of time was spent on just reconciling the numbers. Downstream analysis was hence extremely time consuming and slow to implement.


We created a AWS based data lake to facilitate analytics across the organization.

We interviewed and created a single repository of all the data processing and pre-processing done by different teams across the organization. We helped organize and orchestrate multiple workshops to reconcile different methodologies and adopt singular definitions across organization.

We created linkages with various production systems to regularly ingest data. We leveraged our proprietary ADEF (Automated Data Engineering Framework) – an AI enabled data engineering framework which reduced the ingestion and integration timelines by 45%. We helped implement singular definition across organization.

Analytics environment formed the back bone of all the reporting and analytics across the organization managed through centralized API hub


Centralized data lake helped in driving analytics and reporting throughout the organization. Significantly reduced report creation timelines across the organization – with average reporting taking less than 60% time compared to earlier.