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John Smith
Data Scientist, USA
Cloud-Ready Data
Digital Transformation
Data Governance

What is data democratization?

Data democratization is the foundation for self-service analytics because it enables business users to seamlessly access data that they can use to make informed business decisions. This helps create a data-driven culture throughout the entire organization. 

Large enterprises produce a considerable amount of data every single day. These organizations look to use this data to innovate and grow. However, with data spread out across the organization and trapped in silos, it can be difficult to make data-driven decisions. As a result, many large organizations look to tools, such as a data catalog, to enable data democratization across their business.

What does data democratization help with? 

Without data democratization, business users waste time searching for data, accessing the data, and waiting for approval. This inefficiency is caused by  

  • Data silos: When data is siloed across the organization, stored in different enterprise applications, data warehouses and data lakes, it is nearly impossible for a business user to know where to find the data she needs to do her job.
  • Controlled access to data: While controlling access to data is important from a governance point of view, if only IT has access to the data, it can create a bottleneck. In this scenario, once a business user finds the data she needs, she must go to IT for approval to use the data, which slows down time to insight. 

Data democratization helps combat these inefficiencies by enabling non-technical users to access an organizations’ data without having to ask IT for permission. It ensures self-service analytics and makes it easier for the business to make data-driven decisions.  

Data democratization concerns? 

Although data democratization is an important aspect of becoming a data-driven organization, it does raise some concerns regarding data ethics, misuse of data and compliance. 

  • Data ethics: Many organizations house sensitive and personal data in their systems. Depending on the organization, this data can range from medical history to financial history, to where someone lives and beyond. This data is private and must be treated ethically. With limited oversight and lack of access controls, people across the organization could access this sensitive data. 
  • Misuse of data: In many organizations, IT serves as the gatekeeper of an organization’s data. This creates a “system of checks and balances” that ensures that the data is always being used properly. Without IT in this role, business users may be able to access data they should not have access to and could potentially use data improperly. 
  • Compliance: Regulations such as GDPR and CCPA protect personal data from being misused. If everyone in the company has access to the data, there is a higher probability of someone using the data in a noncompliant manner. This can lead to regulatory fines and penalties. 

How a data catalog enables data democratization

Data democratization tools like a data catalog help business analysts, data scientists and other business users do their job more effectively and efficiently. A data catalog enables users to search for data across the enterprise, find the data they need, trust it and access this data seamlessly on their own. 

To democratize data at scale while ensuring trusted data is accessed and used in a compliant way, organizations must invest in a data catalog with embedded data governance like Collibra Data Catalog. With our governance capabilities, data stewards can create the policies needed to protect an organizations’ data from misuse. And through our ML-powered automation, these policies are applied to data sets without a lot of manual effort from a data steward. Furthermore, Collibra Data Privacy provides policies, guidelines, and purpose limitations to guarantee that data is only accessed by the right people and used in a compliant manner. These capabilities serve as the “checks and balances” needed for data democratization, but eliminate the bottleneck of having IT as the gatekeeper of all data, thus enabling the entire organization to become data and insight driven. 

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