A data democracy describes a methodological framework of values and actions that benefit and minimize any harm to the public or the typical user. Organizations like Data for Democracy, initiated by Bloomberg and BrightHive, and projects like Data for Democracy, established by the University of Washington to help Myanmar transition to a data democracy, are spearheading ideas and debates shaping data democratization.
While specifics on data democratization are a work in progress, agreement exists about some major ideas.
A data democracy breaks down into at least six principles:
- The average end user can access information in any digital format.
- Non-specialists should be able to gather and analyze data or engage in self-service without requiring outside help, specifically from IT.
- Individual private data needs to be protected, as decreed by the General Data Protection Regulation (GDPR).
- Data Quality is a must.
- Technologies such as Augmented Analytics, NoSQL, dashboards, and self-service tools, like those created by Collibra, Teradata, and Unilog, play an important part in empowering nontechnical people in a Data Democracy.
- Data ethics need to guide data democracies.
Other Definitions of Data Democratization Include:
- A “self-service predictive analytics” environment (Paramita Ghosh).
- A context where “employees are aware and participate in Data Governance” (Collibra).
- A situation where “information in a digital format is accessible to the average end user and non-specialists can gather and analyze data without requiring outside help” (TechTarget).
- A beneficial and enhanced relationship between “technology, government, and society” (Data for Democracy).
Businesses are Interested in Data Democracies to:
- Comply with regulations.
- Break down data gatekeeping and silos in organizations.
- Enable transparency in data.
- Enhance the relationships between IT and business.
- Quickly identify revenue-driving insights.
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