Centralizing Data and Resources to Transform into a Data-Driven Organization

GOING DEEPER ON THEIR CHALLENGE

A large international organization was in a high-growth mode, but its IT department was primarily overwhelmed with requests that were small enhancements or bug fixes with minimal emphasis on strategic initiatives.

In addition, there was a misalignment between the business objectives and how IT was deploying resources, which compounded the situation.

Moving toward becoming more of a data-driven organization, the business users have continued to ask the data and analytics teams for more data.  The existing Oracle Exadata legacy data warehouse platform and legacy approach were unable to support keeping up with data requests users have been making.  Managing and preventing issues required a lot of valuable resource time, and the challenges often compounded over time.  This meant that the Oracle legacy data warehouse platform and process made it difficult to keep up with the requests and free up time and resources to start focusing on strategic initiatives that will increase the organizations data and analytics capabilities.

UNDERSTANDING DATA IDEOLOGY’S SOLUTION

The Data Ideology team guided the client in defining the optimal alignment of their IT resources to principal functions in enterprise data management. These functions included data integration, data management, and data visualization. These data management functions were also centralized back under the management of the IT department, with more robust oversight and project management being established.

Together, the client and Data Ideology stood up an analytics center of excellence (ACoE) composed of IT leadership and critical business architects. This new collaboration enabled the alignment of data and analytics projects and activities with the client’s strategic business objectives and goals.

Data Ideology partnered with the client’s ACoE to create a new project intake process. This process was designed to ensure that IT resources, projects, and enhancements were all channeled to the most appropriate resources based on their capabilities and capacity.

To ensure client leadership could manage resource and workload availability, the Data Ideology team established a new estimation and capacity planning process. This was developed as part of the ACoE who would be providing the crucial oversight necessary to achieve success.

Finally, Data Ideology led the implementation of the Snowflake Data Warehouse a modern cloud data warehouse platform that could meet the needs of the evolving data-driven organization, while empowering a strategically aligned IT team.

THE RESULTS

Data Ideology helped this client achieve an extremely high level of engagement with their new centralized data management approach. Central to success was the creation of ACoE and establishing robust systems to support the transform the process.

Their new governance structure and operational controls enabled by the center of excellence approach have helped the organization to reduce the volume of tactical requests. The improvements that drove support for the client’s strategic objectives are now implemented in larger projects, which enable streamlining the management of the organization’s data and analytics resource capacity.

The new ACoE maintains the alignment of the intake process and the available resources and their workload. Also, the client’s IT team has gone beyond “keeping the lights on” to being actively involved with their business peers and working on strategically valuable initiatives that support the entire organization.

Migrating away from the legacy Oracle Exadata environment and leveraging the Snowflake Cloud Data Warehouse Platform has supported the centralization of data across the organization. The Snowflake modern data warehouse platform, combined with a modern centralized approach, was critical to support the data-driven organization of the future.

Success has led to developing the business user data experience and data foundation that future initiatives can build upon further maturing the organization’s data and analytics capabilities.