CASE STUDY 5

A. Data Architecture, ETL, and Warehousing
The first challenge is always that data exists in silos, gathering data from different sources and systems and organizing them in one place is the first step. We help clients manage the process of choosing the right technologies, configuring them and optimizing the performance for their environments. We optimize the architecture for analytics so it would be a powerful tool for business insights.

B. Data Quality Management
Some clients will already existing databases, but their numbers don’t tell the same story; some data is corrupt, some needs a lot of deep dives to understand, and some just doesn’t make sense. The main reason for that is always the lack of Data Quality Management process. We identify process gaps, recommend and implement go- forward solutions, as well as design and implement one-off fixes for current data quality challenges.