A New Era of Data Analysis

by Kojo Beachy-Owusu

If you’re like me, you’ve spent endless hours grinding through spreadsheets full of numbers, scanning for storylines, looking for ways to explain patterns. What happened here? What drove this? What caused that?

And if you’re like me, you’ve found yourself at the helm of an important meeting. In front of you were stakeholders, hungry for answers, and at your back were massive piles of data. And you’ve probably suffered from insomnia, and caught yourself staring at the ceiling, with pressure of these two forces keeping you awake, with thoughts racing through your mind, wondering: isn’t there a better way?

Good news. The answer is yes.

Say hello to a new era of data analysis.

Through advancements in technology, today’s analysis can help you and your teams explore more data, discover more patterns, and ultimately answer more business questions.


Tour deeper, wider, integrated datasets.

Say, for example, you have three data sources:

  • Your sales data,
  • Geodemographics (census data, for example),
  • A Brand Health Tracker.

Historically, you would review a few reports for one source, then the other, then the other. Then, you would hope you understood them enough to pull together a great story for your stakeholders. We’d call this “soft integration.”

To go one step further, you could formally join your data sources together in a process called “data fusion” or “hard integration.” This process puts all of your data in the same place, making it easier to blend insights between sources. But historically, this was labor intensive and somewhat limited.

Today, technology makes data fusion easier than ever before. Now, we’re more able than ever to stitch together disparate data and extract blended insights that simultaneously incorporate all data sources. Data fusion gives you multi-faceted datasets that cover different portions of your brand experience. You can now explore that sales data and census data and tracker data all at the same time. Sounds pretty efficient.


Analyze data through multiple lenses… nearly simultaneously.

You’re once again confronted with that massive pile of information at your back. And now, thanks to data fusion, that pile is much larger than it’d been in the past. How do you work through it?

Historically, you could review multiple crosstabs, disproving one hypothesis after another. Maybe you would try some correlations or build a regression model, just to dig a little deeper. However, your story is limited to the variables you choose to investigate, and the analyses you have time to run.

Today’s data analysis takes those same approaches and essentially puts them on steroids. Thanks to advancements in technology, we can:

  • Examine large datasets
  • Apply multiple analysis methods
  • Execute techniques in rapid succession

You can think less about “can I even do this?” and more about “what is the best way to knock this out of the park?” Today, you can programmatically sift through those huge, integrated datasets quickly – much faster than you and I can work through piles of crosstabs or pivot tables. Instead of running just one type of drivers analysis, we can run five and see how the solutions converge on “the truth.” That allows us to focus on the best, most valid conclusions that point to optimized business decisions. Sounds like a nice way to streamline your workload.


Move your business forward with a wider range of actionable insights.

So now we have bigger, better datasets, and we have faster, stronger approaches to analysis. What does that get us?


The chance to learn something new. The chance to address a wider range of business questions than we could ever answer in the past. The chance to turn new knowledge into successes for you and your team.

Answers are more accessible than ever before, and in places we may not expect. In the retail data space, there’s a well-traveled (and a bit stereotypical) example of this type of work: Dads who buy diapers also buy beer. An insight that makes sense, but requires the right eyes in the right place with the right bandwidth and tools to uncover it.

This new form of decision support has nearly limitless applications. We can impact more than marketing and sales – these techniques can benefit R&D, operations, market expansion strategies, and more. Sounds like a nice way to move your business forward.

To conclude, I hope you’re as excited as I am about today’s analytics tools. We can stop digging through those giant piles of data with our bare hands, and call in those data scientists.

Let’s explore more data, discover more patterns, and answer more questions.

Want to learn more about Burke’s perspective on this new frontier in analytics? Check out Burke’s paper on Geode|AI™ and contact Jamie Baker-Prewitt.

As always, you can follow Burke, Inc. on our LinkedIn, Twitter, Facebook and Instagram pages.

Sources: Feature Image – ©prachid –


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