Data democratization is the ability for information in a digital format to be accessible to the average end user. The goal of data democratization is to allow non-specialists to be able to gather and analyze data without requiring outside help.
When ownership for data is distributed among independent business functions, a sea change in corporate culture may be required before data democratization can become a reality. In some companies, managers may limit employee access to data because they are afraid that non-technical employees won't have the necessary skills to interpret data and apply it correctly. In such a corporate culture, internal data governance policies may be established to only grant access to executives, data scientists and information technology (IT) staff.
Even when an organization wants to embrace democratization, however, there can be impediments to making data freely available. Data may be stored in silos, making it difficult for employees in different departments to access data and view it in a consistent manner. Another problem that prevents the average end user from taking advantage of an organization’s data is that even small data sets may have inconsistencies that have to be cleaned up and files may need to be transformed from one format to another before the data can be used.
Advances in virtualization is making data democratization much easier at the technical level, however, and negating the need for ad hoc, highly labor-intensive processes. Data virtualization software, for example, allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted or where it is physically located.
Data federation software also facilitates democratization by aggregating data from disparate sources in a virtual database so it can be used for business intelligence (BI) or other analysis. The virtual database created by data federation software doesn't contain the data itself. Instead, it simply contains metadata about the actual data and its location.
Cloud storage has proved especially effective for breaking down data silos by creating a central location for data to be stored. Database management system (DBMS) security features can mask or encrypt data to lower the risks associated with data democratization and self-service BI applications can provide non-technical end users with data visualization tools that make data analysis easier to understand. For example, online survey tools with data visualization and reporting capabilities have made it easier for marketing teams to gather and analyze consumer data and share actionable information in real time.
As online tools make data democratization easier to achieve, proponents of the concept believe it will narrow the playing field between big brands and smaller businesses. This in turn, is expected to create new business models, open doors to new business opportunities and transform the way all businesses make data-driven decisions.