Do you really need all of your data tools?
I hope your year has been prosperous both personally and professionally. As 2023 comes to a close, I hope you have weathered this year full of economic uncertainty.
The focus now is on finishing the year-end chores. It’s also a time you can consider data resolutions for the new year. If you’re like most in the IT world, you might have attempted the kinds of data resolutions from my previous posts in 2017 or 2019. Never fear, there is always something to work on.
As the title of this post suggests, I want to look closely at all that machinery that keeps data flowing through your business. As if habit, many of us avoid throwing away tools – even those little hex wrenches scattered around that come with furniture you need to assemble yourself. You always think you will need that little wrench… someday. The data world is different of course, and there are costs to keeping old or redundant platforms around. Here are some categories of data tools you might consider consolidating or removing altogether:
Reporting and Visualization Tools
It does not take long to build a mountain of reports or dashboards once a BI tool like Tableau or Power BI is installed. A problem occurs when departmentalized efforts create their own solutions without considering the enterprise tools already in use. This sounds like that familiar shadow IT stuff. The truth is most companies don’t need (or want) three or four BI tools. Some can stay, but some should go.
Data Movement Tools
Data integration efforts have been a mainstay of the data world forever, so it is expected that legacy tools will exist alongside newer platforms. Some data requires different platforms based on transaction handling or security requirements for example. And of course, some legacy plumbing is home-grown, and people are afraid to touch it. There are many valid reasons to have multiple data movement tools, but they really add complexity to your environment. More complexity = more support = more cost.
Data Governance Tools
Organizations that are committed to data governance will have varying levels of sophistication. Some will track data assets in spreadsheets, and some will use enterprise tools to manage data assets. Some will document data lineage in a dedicated tool while managing data ownership elsewhere. Personally, I think having multiple governance tools is better than not bothering with them at all. But this example isn’t just a nothing-burger. Consolidating real data governance tools will help foster the governance ecosystem that is needed. Data governance is still one of the most difficult practices in data management, so simplifying the toolset is a really good idea.
Now What?
Consolidating your data tools is a chore. It is part housekeeping and part optimization. A good way to address this problem is to start small. Small wins are still wins, and you can schedule them over time. Get a feel for which tools are the most well-adopted across the company and consider going with them. But if those are legacy tools, consider the benefits of having newer technologies and the accompanying skill sets in your organization. Quantify the costs of consolidating vs. not consolidating. If you only reduce your toolset by one, that is one less license renewal.
Best of luck in the new year! And remember, you can do without all of those little, scattered furniture wrenches.