A Modern Data Foundation Spurs Advanced Analytics Expansion

Key Outcome

A healthcare payer's data was severely siloed forcing data science & advanced analytics to spend more time data wrangling than analysis.

How did Data Ideology solve this organization’s challenges?

Challenge Summary

A regional healthcare payer’s data was severely siloed forcing data science and advanced analytics teams to spend more time on data wrangling than data analysis.

Solution Summary

By utilizing modern data technology solutions to properly integrate, manage and present the enterprise’s data, the organization’s data scientists will have the ability to conduct advanced analytics using pre-groomed and tested, reliable data.

Going Deeper on Their Challenge

The data for a prominent health insurance organization was organized in relational databases that could not be easily merged together, leading the data science division to create complex methodology to join this data and spend excessive amounts of time on data manipulation. Overall, this led to a minimal amount of time being spent on analysis.

To make matters worse, data was stored in disparate systems, some with various levels of permissions, leading to difficulty in accessing all necessary data for advanced analytics and posed risks of having users access too much data.

Understanding Data Ideology’s Solution

It was determined that by leveraging MarkLogic Data Hub the client could house all enterprise data in a centralized location and nodes could be added when data volumes increased. Our team also decided to utilize the Snowflake Data Cloud Platform as an additional data layer for user-friendly dimensional models with enhanced security capabilities and data governance features, as well as scalability to increase and decrease bandwidth based on user needs. Finally, the Snowflake models would be loaded to a Power BI server to allow for near real-time data analysis by users with baked-in security levels.

The Results

Data science groups now have the data they need in a format that does not require any grooming, allowing them to focus on advanced analytics instead of data management. At the same time, users now have the ability to combine data from all areas of the enterprise to present a comprehensive understanding of the organization from members to providers and networks. Data is now available on a near real-time basis, and set data privileges ensure that users only access the data they need for analysis.

We were also able to successfully integrate Snowflake and Power BI into a self-service reporting suite which has led to less reliance on IT Reporting teams and greater business buy-in, as business users have autonomy and control over reports.

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