Data Strategy
Having a solid strategy adds value to your data.
Overview
Data Strategy is the 1st of 3 stages in the data management process. In this stage you are deciding how to build out the data ecosystem for your organization. The better your to this phase, the more valuable your data becomes. Because even if you officially just skip this stage, you are deciding to let it happen randomly and your data will be as messy as a toddlers bedroom.
Details
Here are some of the most commonly used elements of a organization's data strategy.
Governance
Governance helps you decide how data will be handled in the organization, from top to bottom. It is a program and involves everyone, not just top leaders and data nerds.
Valuation
Have you done a valuation? How much is your data worth to your business? If it all disappeared tomorrow, would you be out of business? A data valuation helps answer questions like these.
Quality
Data Quality Matters. If your quality is off, your ability to make quality decisions from the technology suffers. The quality of your data directly influences to the quality of your technology products.
Privacy
GDPR, PCI, CCPA, HIPPA, SOX and other others. How are you going to deal with data privacy to protect your team and your customer's sensitive data?
Security
Determine now how you are going to approach cyber security because when an incident happens its too late. A data inventory is very important because its hard to secure what you don't know about.
Metadata
Metadata is the data about other data. It has details about its structure, sources, usage, etc. It provides the details to get the most our of data because it instructs us how to best use it.
Lineage
Where did the data that your apps is using come from and how did it change over time? Lineage helps answer questions such as this.
Literacy
If your team doesn't understand how to use data, they won't use it well. A data literacy program that teaches fundaments about working with data can solve that.