Data Platforms
A data platform is an integrated set of technologies that collectively meets an organization’s end-to-end data needs. It enables the acquisition, storage, preparation, delivery, and governance of your data, as well as a security layer for users and applications. A data platform is key to unlocking the value of your data.
But data platforms can be a complex subject. What exactly is behind a data platform? How do you approach designing one? And what’s the difference between a customer data platform, a big data platform, and an operational data platform?
How to Build a Data Platform
Building a modern data platform needs the right data strategy. Although it’s a large topic in itself, here’s a five-point primer.
Engage the Best SMEs: Organizations should seek the best subject matter experts for the project and bring them to the team. This team will be a mixture of non-technical and technical experts and can often include outside resources.
Focus on People and Processes: Focus on the end user and current business processes. Think about the talent and structures needed for managing and using it.
Gather Business Requirements: Data must address business needs in order to generate real value. The requirements should include end user personas, use cases, existing and possible new data sources, security requirements, current applications and so on.
Build Incrementally: Adopt an agile approach for incremental wins. The entire project may be divided into multiple sub-projects with each small project handling one aspect of the platform or functionality. For example, there may be a project to standardize the data capture tools and another to build a common data sharing capability.
Use What’s Already Available: A data platform arranges and augments existing processes, data for maximum benefit. Start with the data that you already have and implement the workflow that has the greatest opportunity for impact.
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