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Building a Data Maturity Model + the 4 Stages of Data Maturity

A data maturity model that details the different levels of experience companies have with data and how that experience manifests in different areas of the business.

From the article (quoted0:

Stage 1. Explorer - Organizations that are just getting started with data generally do not have a defined strategy for incorporating data into their business. While they may use data for reporting purposes, it is on an ad-hoc basis. They do not source data for these reports and only use internally-collected data.‍

Stage 2. User - ‍User organizations are aware of how important data quality is for success. They make it a standard to use data internally across the organization with the addition of ad-hoc datasets to assist with amplifying internal data sources. Their reactive use of data is convenient for making insightful business decisions. ‍

Stage 3. Leader - ‍Similar to Users, Leaders centrally use data for decision making within their organization. However, they also use data for competitive intelligence. In order to accomplish organizational missions and business success, Leaders use third party datasets in addition to their own data. ‍

Stage 4. Innovator - Data is used for more than just analysis and observation. In fact, organizations that are Innovators are using data to create algorithms and predict how they can stay ahead of the game. With data governance being a part of the entire organizational business strategy, Innovators must constantly utilize data in new ways to adapt to the uncertainty of the future.

Korri Palmer. 2021. Building a Data Maturity Model + the 4 Stages of Data Maturity. Safegraph,