In our work, we often run into problems in clients’ data streams and storage as we are implementing a solution. Instead of a one-time fix, we encourage them to institute sound data governance to help them stop creating bad data before they start a cleanup effort.
Understanding what data governance is and how it differs from data management is sometimes difficult.
Michelle Goetz at Forrester called our attention to a conflation of terms that has muddied the concepts around the two terms. She points out that in an attempt to a simpler understanding, some marketers have made it worse. We are not laying blame here. Vendors want you to use their data management tools, and they want you to use them for good data governance. That’s a good thing.
A Confusion in Terms
The trouble starts with the concepts themselves. Here are the definitions from the WhatIs people at TechTarget:
- “Data management is the development and execution of architectures, policies, practices and procedures in order to manage the information lifecycle needs of an enterprise in an effective manner.”
- “Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. A sound data governance program includes a governing body or council, a defined set of procedures, and a plan to execute those procedures.”
We can understand why the two terms can become conflated. It’s hard to see where one concept ends and the other begins. The reason is they are closely intertwined. But they are separate: good data management requires good data governance, but you could exercise proper data governance if you were still using the processes of the 17th century.
Data management tools are standardized, but configurable to the structures in your organization. Data governance is unique to your organization and its culture.
A Simple Analogy
We think of it in terms of our cooking hobby:
- Cooking management is about the layout and equipment in the kitchen, including all the appliances, gadgets, storage, and fuel supply. It includes the instructions for proper use of the tools.
- Cooking governance is the recipes. They are the rules and procedures we follow to use the tools to create delicious food from ingredients.
Here is data example: ISO 3166 defines two sets of country codes. One set (alpha-2) is two letters, the other (alpha-3) is three letters. Data management is making sure that all the technology platforms can use the same codes. Governance is deciding which one you will use, and ensuring that everyone knows what they are and how to use them.
When Do You Need Data Governance?
The short answer to whether you need data governance is always. People in your organization need to know the rules and apply them to data creation, storage, transmission, and preparation. If your current management structure handles it well, you may not need a formal program and governing body.
Formal Data Governance is required when
- the size of the organization or the complexity of technology outgrows the ability to manage it,
- you need to break down data silos and organizational barriers,
- and when regulation, compliance, or contractual requirements require Data Governance.
Do You Have the Symptoms?
As the use of data become more democratized, the need for governance grows. When IT owned all the data and created all the reports, enforcing standards was easy. Today, almost everyone in an organization creates and uses data. Without governing principles, data becomes chaos.
Here are the symptoms we have encountered in our work.
- You are making bad decisions because of bad information.
- You miss opportunities because it takes too long to get the information you need.
- Your competitors are beating you because you can’t react fast enough.
- You can’t trust your data.
- Analysts spend more time preparing and cleaning data than using it.
- Managing data costs more than it should because you have to spend so much to correct it.
Get Started Now
We urge to you resist the urge to run out and buy a software package. You will need it, but you will not be ready for the decision until you complete an assessment of your current data. The place to start is to understand how much bad data is costing. Read our article on the cost of bad data to learn more.
2. "The Basic Information - The DGI." Accessed August 26, 2016.
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