Data Democratization is Finally Living up to Its Name
Data democratization is the idea that digital information should be accessible and understandable to the average end user as a basis for decision-making. Data democratization has been promoted as a competitive advantage in the global economy and a desirable, egalitarian end-state where all decisions are data-driven. But has this been the reality?
In practice, I’ve found this goal of broad access has been isolated to corporations and corporate data. Most articles on data democratization quickly move from statements about accessibility to a narrower focus on organizational initiatives making data available to employees. That implies a restricted scope for data democratization, specifically not within the public domain, but limited to private sector organizations. Mostly, data “democratization” has been a buzzword for “data accessibility” with no public involvement or collaborative data use.
Until now. Today, we’re seeing broadening data democratization through the rise of user-friendly public data (such as ); organizations providing content through programs like OpenNASA, which makes all of NASA’s open data, code, and APIs publicly available, or OpenData500, tracking the use of public data; and citizen data scientists.
When I began my career, data was handwritten onto paper, entered onto punch cards, and read into a computer. Programmers extracted that data, turning it into user reports.
By the mid-1980s, many business users had access to personal computers, spreadsheet software, and business reports for budgeting and forecasting. While these users and their data were typically isolated from IT, creating silos distinct from the core business systems, they knew the business processes and context for that data.
Subsequent decades brought new data storage alternatives (such as databases, data warehouses, and data marts). These included applications to capture incoming data and provide consistent business processes and specialized interfaces such as extract, transform, and load (ETL) and business intelligence (BI) tools to connect the data among applications, databases, and the spreadsheets still actively used. At times, standards emerged for certain categories of tools (such as SQL), but accessing data was the technical experts’ domain, while business users applied data for business purposes.
