According to Statista, a leading provider of market and consumer data, the four C’s of global data—created, copied, captured, and consumed—are expected to almost triple between 2022 and 2025 from 67 to 181 zettabytes (ZB). One ZB equals one billion terabytes (TB). Your organization is likely contributing to this statistic, as companies everywhere are experiencing rapid growth in the four C’s of data. The question is whether they’ll be able to manage and leverage the opportunities the data offers.


Unlocking the power of this data requires getting the data into the hands of users. For companies, that means adopting a data democratization strategy. This column explores the meaning of data democratization, its pros and cons, and how management accountants can help their organizations create value by implementing a data democratization strategy.


Historically, an organization’s IT department and computer specialists controlled access to its data by serving as gatekeepers monitoring and limiting data access then distributing it to users by request or preconfigured access. Data democratization removes this roadblock by opening direct data access to users and eliminating the IT intermediary. In other words, it means an organization’s data is available to everyone without the IT department’s involvement. A self-service data access model gets data into the hands of users faster and provides them with the data they need. Users don’t have to jump through hoops, possess tech skills, or rely on data scientists or programmers to access data. Citizen data access trumps technical training access. Access becomes transparent, fast, and easy; users are no longer dependent on the IT department or an AI computer.




The clear advantage for data democratization is getting the data into the hands of the decision makers. This creates a competitive advantage because more employees will be able to access the data to provide better insight into decision making. As users become more educated about their data and how they can use it, they can become proactive about data needs and define new data sources instead of being limited by traditional data sources. Nontechnical users who might have previously been shut out of decision making can bring their minds and experience to the decision-making table. And the opportunity for cross-functional data sharing soars.   


Disadvantages include data integrity challenges because the three V’s of Big Data—volume, variety, and velocity—may be affected. Data must be managed, cleansed, controlled, and organized. Otherwise, data could be misinterpreted, leading to flawed decision making. The risk of garbage-in, garbage-out is magnified with bad data. There will also be a learning curve because traditional users who may have suffered from data fatigue caused by hassles and frustration in previously accessing data may now need to relearn how to access and trust newfound data freedom.


Security risk is critical because opening the data floodgates could lead to unauthorized data use and sharing. Data democratization doesn’t mean unlimited open data access; it means controlled data access that won’t compromise the organization.




Implementing data democratization must be a deliberate, strategic process to balance leveraging and safeguarding data. A 10-step plan could include:


1. Hiring a chief data officer (CDO) to develop and manage data strategy, to create a data architecture plan, and to oversee analysis and business intelligence applications. Smaller organizations can define the function and assign the responsibility to the CFO’s or controller’s department or engage a consultant.


2. Performing a data audit to identify data sources (internal and external), current use and users, authorized use by source and user, and security level by source and user. Prepare a data source dictionary to document the findings. The document becomes the foundation of the organization’s data democratization policies and procedures. Users should be an integral part of the process to ensure the audit is a baseline of data requirements and usage. It can also be used to perform a gap analysis to identify future data needs.


3. Establishing data governance policies and procedures. Without clear data access policies, data democratization could cause more harm than good by risking unauthorized data access or confidential data disclosure. Strong data governance, data security, and internal controls must be spelled out to safeguard data. Include limitations on data use and sharing to protect data assets. Strictly enforce violations and punish violators.  


4. Selecting and deploying a data platform and tools for data access and sharing. The sophistication of both depends on the organization’s budget. Smaller organizations might set up a desktop data server or explore external hosting services, while larger organizations could create a data lake or store data in the cloud. If the organization lacks technical talent, enlist a consultant.


5. Converting data from the data platform into user-friendly formats so it’s ready for immediate analysis. Access to data that’s extracted in a technical format defeats the purpose of data democratization and perpetuates frustration users experienced under an IT-controlled environment.   


6. Performing an ongoing data quality review to eliminate duplicate data, verify data integrity, and correct errors. Nothing undermines the value of data more than multiple versions or errors. Automate the process to take advantage of data rules and data quality standards goals.


7. Providing data analysis using a dashboard visualization tool like Power BI, Tableau, QlikView, or Google Charts. Address performance considerations to ensure users aren’t left hanging as they wait for information to load.


8. Developing training programs to educate users about data sources, organizational needs and opportunities, how to use data retrieval tools, and how to analyze and interpret data by upskilling the staff. While all are important, teaching the team how to interpret data is the key to creating value.  


9. Fostering a data-focused culture to empower users. Raise the organization’s data literacy level and encourage cross-functional collaboration.


10. Balancing data democratization with protecting data assets. Follow the pulse of the technology explosion to identify how to safeguard data and to confirm the intent of how it’s used.


The key to data democratization is data literacy. If users don’t understand their data, its power goes unharnessed. As Jonathan Rosenberg, Google’s former senior vice president of products, says, “The democratization of data means that those who can analyze it well will win,” leading to value creation. And as management accountants know, the numbers don’t lie.


The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of the Air Force, the Space Force, the Department of Defense, or the U.S. Government. Distribution A: Approved for Public Release, Distribution Unlimited. USAFA-DF-2023-297.

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