Data Strategy: The Difference Between Collecting Data and Finding Insight

For many businesses, data is little more than a byproduct of day-to-day operations. Those organizations miss out on a wealth of benefits and opportunities that lie hidden in the data they’re already collecting. Deriving value from that data depends on developing a data strategy—defining how data will move past simply existing to truly supporting the organization.

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What's Included

Why data strategy matters

Data has no value until it serves your organization, and without a data strategy, you’re basically operating an information slot machine—every now and then you’ll hit on insight, if you’re lucky.

What data strategy includes

A data strategy includes an array of concerns about how your data is ingested, stored, accessed, shared, visualized, kept secure, and applied to the complex questions you want to answer to move your organization forward.

How to get started

No matter the inspiration, a data strategy helps you lay the foundation for a sustainable, scalable, simple data program. And it always starts by figuring out where you stand right now through a data maturity assessment.

Key Facts

  • A successful data strategy is not a unilateral effort. It requires input and buy-in from leadership and stakeholders.
  • Data strategy affects the entire organization. Which means everyone should be involved, whether by answering questions about data usage in the discovery stage, collaborating on priorities, or helping to lead change through implementation.
  • Different departments speak different data languages. Spanning the systems, processes, and data cultures from team to team is critical for developing a strategy.
  • Setting expectations smooths your path forward. Showing your teams a defined strategy lets them know they’ve been heard and their problem will be addressed.

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