Data Strategy

A data strategy defines how an organization will use its data assets to support business objectives. This involves assessing the organization’s current data landscape, defining a vision for the future of data, and creating a roadmap for how to get there.

Maturity level, architecture, budgets are already some topics that should definitely be discussed. What was the initial budget? Does our data strategy fit within this budget? Should we adjust the budget or adjust the data strategy? Organizing workshops which can have both a functional and technical background helps to make this concrete. Together we arrive at a roadmap where everyone feels comfortable.

Why is Data Strategy useful?

A well-defined data strategy is essential for any organization that wants to effectively use its data assets to support its business goals. It helps to ensure that data is collected, stored, and used in a way that is consistent, reliable, and aligned with the organization’s strategic objectives.

The key components of a data strategy

Identification

Identifying data, and recognizing its meaning and usefulness, is an indispensable requirement of a good data strategy. After all, using and processing data is not possible if it does not have a name, is not in a specific format and has not been assigned a value. An organization must describe (meta)data so that it is recognized.

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