Tools and Technology in the Planning Phase

We saved the tools and technology for last in our Data Governance blogs series because it’s easy to get distracted by the shiny object of software (and software sales) and the big promises that it makes for how it will transform your data governance and your life. 

If you have gone through the earlier steps, or at least the beginning phases, and thought carefully about your people and your processes, you are only now ready to think about new tools to support those people and processes. 

What are signs that you need to use a tool for your data governance? 

• You need a place to store the decisions you’ve made, the documentation you’ve done, or the policies you’ve created. This is most organizations, and the most important piece of using a tool for this is to get it out of people’s heads and somewhere it can be stored and referenced. 
• You need to communicate about your data and your data governance, for example to discuss data quality issues, share policies, or let others know about those decisions. 

You want to make sure to identify tools and technology that SUPPORT the processes and decisions you have put in place. And to support the people who carry out those decisions. Use the processes and people to guide your tool selection. Don’t let the tools and technologies drag your processes and people around by the nose.

What kind of things might you consider using to support the hard work you’ve done on your data governance strategy? Here are a few examples: 

For your data catalog:

This is essentially a tool that you use to keep track of all your data and reports to share that information with others in the organization. The tool itself could be anything from a spreadsheet with a row for each data source, to something fancy and higher-end like Atlan. 

‍For your data model:‍

As a reminder, a data model organizes data elements and standardizes how the data elements relate to one another. Data models aid communication between the people defining the requirements for a system and the people defining the design in response to those requirements. They are used to show the data needed and created by organizational processes.

Remember, data modeling is “the process of creating a data model for the data that will someday be stored in a database”. 

You might use something like Lucidchart (our tool of choice) to diagram these relationships. You could also use any other graphics tool, or even something that is connected to the database or data source you are modeling, like MySQL Workbench. For more information about making an actual Entity Relationship Diagram with your tool of choice, start with a video like this one. 

Metrics scorecards:

We discussed having data quality metrics, and a way to keep an eye on them. Once you have done the hard work of deciding on and defining your data governance metrics (you did do that, right?) you want to report on that information in a way that has high visibility, so people can see early and often where there are data quality issues. You can use something like PowerBI, Tableau, or any other BI tool, or you can keep it simple and put those metrics in Excel. Excel visualizations are more powerful than many people realize. 

So how do you decide on which tool in the planning phase? 

• Try to start with something you already use within the organization. Just because a tool might be a bit better, that doesn’t mean it warrants the cost, time, and aggravation of learning something new. The proliferation of tools is no joke; it can create resistance to doing data governance, and result in a “tool graveyard” of software that goes largely unused. 
• That said, don’t assume something is the best fit just because someone is already using it. Make sure you are clear about what you need the tool to do so you can assess whether your existing tool fits the bill. 
• Speaking of understanding tool requirements, get advice from people who already use the tool you are considering, and test out anything new to the organization with a few early adopters. From there, test and test the tools again. There are always a few people in any organization who love to test and try out new things, and they can save people who love to stick to the tried and true from a lot of suffering if you take advantage of them early in the process. 
• Make sure your tool will scale. If everyone in the organization will need access to it, make sure you can afford all the licenses, store it on a central server, or otherwise make it available to everyone so your metrics don’t end up in a dark corner of the organization. 

No matter what tool you use, never forget that your people and processes should drive the selection, training (you didn’t forget what we said about training, I hope), and implementation of the tool, not the other way around. 

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