HOW DO YOU DEMOCRATISE YOUR DATA?
Set up data infrastructure:
Create/set up data storage, platforms and analytical tools depending on your end usage with the core components of democratization in mind. Apply FAIR (findability, accessibility, interoperability, and reusability) principles to all data over time.
Restructure your team:
Move towards a decentralized data team, where any team has the ability/knowledge to perform the role of a data scientist
Implement Metadata Hubs:
A Metadata Hub is part of your infrastructure that goes a long way in enabling your data to be democratized. Metadata Hubs help in enabling data to be accessible by indexing datasets, contents of tables, and their connection to other data. Using semantics allows any data used to understand the origin, context and historical use of a data source before they decide to work with it.
Quality checks and data stewards:
One of the biggest challenges in decentralizing data is maintaining the quality of the datasets created by different teams and ensuring consistency. Open data formats, in-house QC tools and automated checks and anomaly detectors go a long way in helping with quality checks. Data stewards can help in implementing data governance standards for democratized data to ensure the quality of content and metadata.
Realigning focus by training your team on ETL:
Having a decentralized team helps users perform Extract, Transform and Load operations on their own data, instead of having to rely on IT teams and Data Engineers. This reduces the burden on data engineers who can work toward more organizationally relevant ideas for improving and maintaining data infrastructure. It creates an agile process for business units to have analysis-ready data whenever they need it.