As I write this article, my newest daughter is turning one month old today. If you’ve wondered where my blogs or vlogs have been, you can now read in between the lines. She’s a sweet gift, and I’m finding my affections for her are continuing to grow every day. Frankly, though, being a parent is hard! While the joys will always surpass the struggles, it is nevertheless a daunting task that will continue for years to come. The experience may seem at times to be draining and discouraging, but the reality is that I wouldn’t trade the difficulties, the late night feedings, or the hourly-long crying sessions for anything in the world.
In many of the same ways, data analytics can be an intimidating task. There will be struggles, brain-nourishing sessions, and sometimes hourly-long crying sessions on your part. But as with every grandiose goal, there are greater opportunities and gifts awaiting. If you are reading this now and are discouraged at where your company or department’s current data-maturity life cycle resides, don’t dismay. Have the end goal in mind, and set small incremental steps to get there. Remember that each minute is a gift, and there are lots of things to enjoy along the way, even before taking baby steps.
Today I will be writing to you about the greatest barriers to data analytics in our current business environment, applicable to both large corporations and small businesses. As a disclaimer, there may be more nuances to these barriers that I may miss along the way. It’s also possible that you work with regulatory compliance issues. These are real issues, but for today’s blog I’ll be taking a more generalized approach. With that said, let’s dive in!
Barriers
One of the many great devices for memory is something called a mnemonic. To help you remember four of the greatest barriers to data analytics, remember PASS. If you want to create a sentence that may help, think of something like, “Resolving the four barriers will help me PASS.”
PASS
Platform
This is another word that can mean the tools used to get the job done. It can also be referred to as architecture. If you don’t have a database to store the data, you won’t be able to gain any meaningful insight whatsoever. If you don’t use a Business Intelligence tool like Power BI or Tableau, you won’t be able to visualize the data appropriately. Consider what your end goal is and work backwards.
Access to the data
Sometimes the data you need may be hard to get; in other cases in may be non-existent. Figure out what kind of data you want to use to make meaningful decisions, and take small steps to figure out how to get it.
Subject Matter Expertise
Many data experts may be great at all the hard skills needed to work a particular database or BI tool. However, a subject matter expert who really knows the data will help give lots of advice on how to interpret the data for greatest gain. Consider what kind of consultant or advisor may be most helpful for your current needs.
Someone to do the work
Lastly, you need a data expert or someone with the skills to crunch the proverbial numbers. Find someone that can build you what you need.
I hope this small article helps you remember the greatest barriers you will likely face when trying to advance your data maturity life cycle. If you have any questions, comments, or anything else to add, please don’t hesitate to reach out.