Data Strategy & Governance

Data strategy & governance

The urge to manage, protect and organise data uniformly and systematically becomes more prominent as enterprises seek to harness the power of data to fulfil various consumer and business needs. Several reference architectures and/or methodologies exist to implement strategy and governance around data – Data Hub Architecture, being one of them.

A data hub aims at consolidating data from different sources and formats into one common platform, thus, eliminating redundancy and data silos. Data is moved, stored, harmonised, indexed, catalogued and protected with appropriate security controls at each step. This helps in building good governance around the data. Trusted and secured data is made accessible to a variety of applications and users from the data hub.

Applications

  • Any data
  • Source for AI, ML & many such applications

Benefits

  • Diverse, scalable and robust data platform
  • Data harmonization
  • Enhances collaboration and connectivity
  • Removes data silos

Considerations

  • Requires thorough brainstorming of data and users 
  • Security implementations should be done thoughtfully

Our offerings

Data modelling & design

  • Understand the various data sources and usage
  • Understand the association between datasets, constraints etc.
  • Create appropriate and optimised models and design for the datasets

Master Data Management (MDM)

  • Understand various datasets and their attributes (fields etc.)
  • Understand various rules, constraints and associated processes for datasets
  • Suggest/Implement an MDM solution with performant tools and technologies
  • Suggest/Implement ML (machine learning) techniques for MDM

Data Discovery & Cataloging

  • Understand various data sources and their structure
  • Discover relationships between the different datasets
  • Suggest/implement data cataloguing using appropriate tools and measures
  • Suggest/implement automation using ML (machine learning) techniques

Data Security Policies

  • Understand the datasets and accessibility to users or roles
  • Suggest/implement privacy measures like encryption etc.
  • Suggest/implement appropriate authentication schemes
  • Suggest/implement appropriate authorization policies for data