Our company is exploring the possibility of using more Big Data. Is it really worth the investment of time, systems and resources? Or are some of its highly touted advantages actually just hype?
When it comes to the way we’re able to capture data these days, bigger is indeed better – because Big Data, higher volume, faster velocity and great variety, truly do allow businesses to significantly improve their processes and operations and ultimately can have a huge impact on the bottom line.
Just don’t make the mistake of confusing data and information with insight.
But doesn’t Big Data’s information lead to major insights?
Most likely, but not automatically.
It can if it comes from the right kind of data and if that data is being analyzed by professionals who understand the ins/outs of your business and are able to extract actionable findings. Unfortunately, too many businesses’ Big Data initiatives still overlook one or both of those major “ifs.”
So, what kinds of things make data the “right” kind that you’re referring to?
For one thing, any data you collect should be ethically acquired, including confirming that it was obtained via methods that were in full compliance with individual privacy laws and that its collection didn’t compromise sources’ cybersecurity, confidentiality, or trade secrets.
For another, you want to be sure that it’s free of bias and that there are enough checks and balances in place to weed out information that’s redundant, rife with inaccuracies or based on faulty methodology.
And what kinds of professionals are best suited to work with Big Data?
We covered a lot of this in our July 2009, 2022 Ask AFS feature, “What Should You Look For In A Data Analyst?” and in our October 2022 Logistics 101 feature, “Logistics 101: Computational Power Vs. Brainpower,” both of which we highly encourage you to read. However, if you’d prefer some advice that’s more up close and personal, shoot an e-mail to our Chief Analytics Officer, Mingshu Bates, at [email protected]. She’ll be happy to walk you through some best practices and skills to look for when building a winning analytics team.
