Data Maturity Model

Achieving Data Confidence results from executing four core enterprise data management processes with process maturity: Govern, Architect, Assure, and Share. It is only through maturing capabilities in all four of these process areas that enterprises can achieve Data Confidence, which is essential to achieving Open Government goals and to improve services to the citizens.

Maturity Gap

Lack of maturity in data governance can leave the federal enterprise vulnerable to a number of risks, all of which ultimately impact the quality and timeliness of services to the citizens:

• Limited enterprise situational awareness
• Weak collaboration
• Questionable data quality
• Data security risks
• Limited strategic thinking and planning
• Unreliable predictive analysis
• Data silos
• Data incongruity
• Limited information sharing
• High maintenance costs (redundant data centers, applications, and databases; unknown architectural dependencies)