Step 4: Identify the
right technology for self-service data access

A crucial part of fostering a data-sharing culture is democratizing data and enabling users to find and use reliable data independently. This can be accomplished by providing various tools and features that simplify data discovery, comprehension and access. Identify the technological tools and capabilities required to support your pilot use case. Which ones will you need to deploy to overcome the data sharing challenges you identified earlier?

Centralized data catalog: Provide an inventory of data assets from various sources across the organization, complete with relevant metadata (such as classifications) offering helpful context
Business glossary: Define and manage business terms to facilitate a common understanding of critical data concepts. Improve data literacy and facilitate effective communication among data stakeholders

Automated data lineage tracking: View where data originates, how it has been transformed and where it is eing used across various systems and processes
Data quality assessment and monitoring: Determine data quality rules and metrics and automatically evaluate data against those standards to gain insights into data quality issues and areas for improvement
Data policy management: Create and maintain policies related to the collection, access and usage of data to help ensure that it is utilized and shared appropriately and in compliance with internal standards and external regulations
Data sharing agreements and contracts: Establish clear agreements outlining acceptable use cases and terms for data sharing

Data marketplace: Allow users to shop for curated data products easily, reducing reliance on IT or data specialists
Data access request management: Automate data access request mechanisms to streamline access and minimize delays while complying with relevant policies at scale
Collaboration: Enable users to share knowledge, certify data assets and discuss data-related issues. Provide tools for workflow management to help stakeholders collaborate on tasks and simplify processes, including documenting data assets
Data querying: Allow users to query data across sources to view and better understand its contents
Data masking: Protect sensitive data so only the right users can access it