A Fortune 500 health insurer’s growth strategy through acquisitions was hindered by the limitations of data integration and data sharing with newly acquired companies. They engaged Object Partners to define and implement a unified enterprise-wide data strategy.
Our client struggled with siloed and inconsistent data, lack of a centralized location for data, and no clear patterns between departments for ingestion and consumption of data. In addition, newly acquired companies had different data strategies, making it difficult to unify their efforts and bring products to market efficiently.
The OPI team established a general scope for a new modern platform and developed a technical design and implementation strategy. OPI designed and implemented an architecture to create an enterprise-wide data fabric, a self-service data mart, advanced analytical capabilities, and that would allow other integrations down the road.
We identified the full scope required to accomplish the client’s goals, and identified the design required to set up Snowflake and Azure environments. We helped define business functions behind over eight canonicals and their sources. The combination of Azure and Kafka allowed us to dramatically speed up ingestion of data to Snowflake from many various sources.
We created a centralized data services hub to establish an enterprise-wide data fabric. Snowflake provided the back-bone, serving as the data warehouse for the system. We also provided the ability to create a self-service data mart from this data warehouse. This allowed for easy access to the data provided by this system.
Along with the data warehouse implementation we constructed various ingestion and consumption methods to be used in combination with Snowflake. We constructed software that allowed for easy management and creation of various custom APIs for data stored in Snowflake. This helped streamline development and reduced any issues when we encountered setbacks. This implementation allowed us to teach the current engineers to use technology to automate tasks they would previously manually do. We also built a number of different self-service tools to help their data engineering team manage new requests to the platform.
The client’s new architecture eliminated years of technical debt. The new platform allowed our client to contribute to the larger enterprise more quickly and created a set of ingestion and consumption patterns to allow for easier access to data enterprise wide. The project also identified business gaps in the organization so they could be addressed, helped eliminate the siloing of data, and created a unified approach to handling the enterprise’s data.
Our client now has a centralized location for all of their data. They have the ability to integrate with a Machine Learning Platform, a self-service data mart, and advanced analytics, and more flexibility to grow with their business capabilities. This modern platform provides data from various departments and acquired entities to other realms of the organization, giving them the tools to make smarter business decisions.
The OPI team understood the business needs and aligned the right team resources to implement the solution, including Platform, Microservices and APIs, and Snowflake and Modelling Teams. We involved the right internal client teams to allow for easier transition of the platform and brought them up to speed on the new platform technologies so they could manage and maintain the project for the long haul.