Vol #19 | What is Data Maturity
and why do enterprises need to understand their maturity levels?
Hello Data World - I hope you are doing great and enjoying your work!
Every enterprise aspires to become a “data-driven” organisation in today's world. To become “data-driven”, it is important for the data team to understand their data maturity levels.
In this week’s post, I’ll explain what is “Data Maturity” and why organisations need to assess their maturity levels. As always, I’ll try to keep it short and simple!
Audience - Data Architects, Data Leaders, Tech PMs
Technical Level - Beginners
What is Data Maturity?
Data Maturity is a measure of an enterprise’s ability to leverage its data using the best practices.
Data Maturity covers multiple aspects of “data and the organisation” creating and managing this data. Some of the key aspects are listed below.
Data Management - How does the enterprise store, manage and share the data within the organisation? Is there a well-defined data strategy and architecture for the data platform?
Data Governance - Is the data governed, secured and access controlled? How well is the Data Governance strategy defined, reviewed and followed?
Data Consumption - Is the data leveraged to generate insights and perform analytics, forecasting, and other predictions using advanced analytics and machine learning initiatives?
Data-Driven Initiatives - Does the enterprise have a data-driven mindset and data culture to leverage data to the best of its capabilities?
Data Maturity has three main parameters - Data, People, Process
It is a measure to understand how well the Data is used by the People dealing with it by using standard, well-defined Processes.
What is Data Maturity Assessment?
To understand its maturity levels, organisations need to do an assessment. This activity is known as Data Maturity Assessment (DMA)
Data Maturity Assessment is like an ongoing audit to review an organisation’s processes related to data management, governance and usage.
Data Maturity Assessment is done across various categories. The key categories are summarised below.
Data Strategy & Data Architecture
Data Governance & Data Quality
Data Platform & Data Management
Data Operations & Other Common Services
Data Security
These can differ from organisation to organisation, but broadly these are the various areas where assessment needs to be done.
There are various models and approaches for performing the assessment. You can reference the DMA frameworks from leading institutes like CMMI, DAMA or EDM.
Based on the assessment, the maturity levels can be decided. Like the maturity assessment areas, these also differ based on the frameworks used. However, these can be broadly categorised as
Beginner - Organisations that have just started their data journey and implemented some basic processes.
Intermediate - Foundational processes like data management and security are set. Other processes like Governance, Operations need more focus.
Advanced - All processes are well-defined, reviewed and followed by all departments across the organisation. All decisions are data-driven.
Leader - Have the “best in industry” data practices that can be used for references or benchmarking by other organisations.
Maturity Assessment is important for any organisation to understand its current levels, plan its progress to the next levels, and make them a data-driven organisation.
I hope this article has helped you start with “Data Maturity”. This post is public, so feel free to share it with your friends and other data people.
Thanks for reading Data & Cloud! Stay Tuned for more such articles.