Cloud Based Data Warehouse (HIPAA)

Vicert developed an automated solution which reduced the risk of human error and updated latency. Now, all changes made to the data and code are tracked, which gives the ability to comply with any new regulatory updates.


Our client’s business model depends on their ability to efficiently collect, safely store, and cost-effectively process a large quantity of data.

They turn conversations between patients and providers into proprietary data sets, analyze these sets to assess key trends, and then sell the access to analysis results.

The Electronic Data Capture (EDC) tools in use were identified as the key problem: bad user interfaces produced error-prone data entry.

This required hundreds of hours per month for data corrections and pre-processing instead of profitable data analysis.

Those tools also did not fully support downstream needs, but complicated them instead, while limiting key capabilities.

Our client needed a solution that would act as a Data Warehouse (DW) and a single source of truth for the observational data they gathered, all while enabling the automation of data entry, pre-processing, and analysis.

Cloud Base Data Warehouse


We designed a solution that provided a single source of truth for all data, while logging any changes to the data, and tracking changes to the code used for the data analysis.

The solution runs on the cloud (AWS) without needing any on-premise infrastructure.

The system was designed to support regulatory compliance with applicable regulations (HIPAA, 21 CFR Part 11) and to the level that meets business needs.

The programmatic controls of configurable user permissions are deployed in the data environment to ensure restrict users access to the right data. Furthermore, the architecture enables the easy addition of new data registries/cohorts.

The process of the historical data migration from the set of data files into the warehouse was included in the solution design and documentation, while the logic to allow the switch-over from current data sources was also included in the solution.


The automation reduced the risk of human error and updated latency. All changes made to the data and code are now easy to track, which gives our client the ability to go back and update compliance with any new regulatory updates. Gone is the old error-prone and time-consuming process where our client’s analysts were copying data from different EDCs and historical data files to a local machine and then running data manipulation scripts.

With this, we prevented:

● possible exposure to data integrity risks
● potential compliance gap
● the existence of divergent data sets and data silos inaccessible to all teams

The processing of all historical data was switched from manual to automatic so it can be easily leveraged in further research. The continuous delivery integrated into the solution provides the infrastructure to change the solution’s environment (and even add new environments down the line) with low cost, time, and risk. The solution supports:

● adding mobile apps
● artificial intelligence
● speech recognition
● EMR integrations
● other modern tools down the line