By adopting best practices for data democratization, organizations can avoid the pitfalls of the past
Data democratization can be defined as making digital information accessible to the average non-technical user of information systems, without having to require the involvement of IT. It is the foundation for self-service analytics, an approach that allows these less than technical users (ie: line-of-business) to gather and analyze data without having to seek help from a data steward, system administrator, or someone in IT.
This trend is continuing, with recent research from MIT Sloan Management Review reporting that more than 77% of respondents reported an increase in access to useful data since last year.
The benefits seem obvious so why hasn’t this happened sooner and what is allowing it to happen now?
Barriers to access
Data in silos:
Enterprises have seen some success in getting their data into data warehouses, data lakes, or business intelligence systems. That solves the storage problem. But with data stored in multiple silos, it is difficult for an enterprise to establish a single source of trusted data that everyone can rely on. What’s needed is the establishment of a data inventory.
Related to the problem of not being able to find the data is the problem of not knowing whether or not you can trust it. The old way of dealing with this is to establish a system of top-down governance where IT manages the data, ensures data quality, establishes business rules and performs analysis. Typically, access controls are provided to established administrators. But by erecting a wall between the people who managed the data, ensured data quality and performed the analysis, and the business users who needed to act on it, they didn’t allow for the free-flow of information necessary to move with agility.
Existing business intelligence and data analysis tools just weren’t designed for the self-service analytics world we find ourselves in today.
Crawl your sources:
Wouldn’t it be great if you had a way to search across all of your data sources to find the information you need? And wouldn’t it be even better if, when doing so you could use the same natural language search capabilities you use when doing a search on Google? A data catalog does just that, providing you with a catalogued inventory of all of your data assets while allowing everyone on the team, data analysts, data consumers, and data creators to collaborate.
Make Everything Accessible:
Freeing up access to your data by taking a more grassroots approach to data management and governance means everyone in your organization, not just your IT group can easily find, understand, and collaborate on the data they need to make impactful business decisions.
The latest generation of data visualization and reporting tools have democratized access to data and are only slightly more complicated to learn and use than the spreadsheets and charting apps that preceded them (but with much better visualizations). These tools have leveled the playing field and provided an even greater need for a data catalog to support them. Data catalogs play well with self-service analytics tool by providing a tool-agnostic approach to data cataloguing. You can use the a data catalog to search your enterprise data sources and BI tools and to learn how the data assets they contain are being used within your organization. A data catalog injects the metadata along with the tables, schema, queries and other data. By adding human collaboration to the mix, more modern data catalogs go beyond a simple data inventory, allowing everyone to hold conversations around the data, improving its quality along the way.