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Innovations in Data Capabilities

by Uday Kumar, Chief Digital Officer

January 7, 2022

Innovations in Data Capabilities

#Innovation in the data space continues its disruptive march and this won’t slow down anytime soon. It is not easy keeping things simple or being able to wrap your head around the main moving parts in the data ecosystem. So I took a stab at white-boarding a data capabilities mental model. Here are a few notes to explain my thinking –
  • Data storage is the most basic capability for the purposes of persistence, backups, and restores
  • Data Lake allows a smarter architecture to store all kinds of data in raw format that can be used for operational use cases
  • Data Warehouse allows store data in processed format that can be used for analytical and reporting use cases
  • Data Governance capability is what keeps everybody playing by the rules (compliance, security, privacy, etc.)
  • Data Engineering is how you move data around (probably the toughest one of all based on my experience)
  • Data Analytics is the capability to analyze, summarize, and visualize data to understand performance
  • Data Science is the capability of extracting useful insights from unstructured data (AI/ML are subsets of this capability)
  • Finally, what you don’t see in the model are any mention of product or operations. Both of those are “implied” characteristics of each data capability; you can’t stand-up any capability without either of those.
Question for you: What is missing from the picture or my notes? Do you have a mental model you would like to share? #dataarchitecture #datastrategy #datascience #datanalytics #dataengineering #datagovernance #datastorage #datalake #datawarehouse #mentalmodels