In Defining Terms, we go deep on the topics, trends, and hotly-contested debates that matter most to data, analytics, and business intelligence professionals.

The sheer quantity and scope of data produced and stored by your company can make it incredibly hard to find the insights you need to steer your company. This is where Business Analytics (BA) and Business Intelligence (BI) come in: both provide methods and tools for handling and making sense of the data at your disposal.

What’s in a name? Business Analytics

Here’s where it gets tricky. BA and BI are broad terms covering all kinds of technologies and approaches — and, to add to the confusion, are often used interchangeably.

So…what is the difference between business intelligence and business analytics? Is there a difference at all?

Let’s take a closer look.

BI and Analytics for Data Engineers

Defining “Business Analytics”

BA is a catch-all expression for approaches and technologies you can use to access and explore your company’s data, with a view to drawing out vital insights to improve business planning and boost performance.

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and make educated guesses about how things will pan out in the future.

Defining “Business Intelligence”

BI is also about accessing and exploring your organization’s data. And, again, the ultimate goals are to better understand how the business is doing, make better decisions, improve performance, and create new strategic opportunities for growth.

But on the whole, BI is more concerned with the whats and the hows than the whys.

BI is about accessing and exploring your organization’s data.

BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining, online analytical processing (OLAP), and reporting as well as business performance monitoring, predictive and prescriptive analytics.

In other words, both BI and BA are tackling the same problems, but if you’re working with masses of raw data, you want extensive control over how you use that data, and you want to draw out your own interpretations and conclusions from the numbers, the tools and techniques you use will likely fall under BI, rather than BA.

The BI/BA debate

Case closed, right? Unfortunately not: there’s no real consensus on exactly what constitutes BI and BA, or where the lines are drawn.

Predictive vs descriptive

One way to look at this is that BI tells you what happened, or is happening right now in your business — it describes the situation to you. Not only that, a good BI platform describes this to you in real-time in as much granular, forensic detail you need.

So, BI deals with historical data leading right up to the present, and what you do with that information is up to you. Your expertise and judgment are crucial.

BA primarily tries to predict what will happen in the future. It combines advanced statistical analysis and predictive modeling to give you an idea of what to expect so that you can anticipate developments or make changes now to improve outcomes.

Both approaches are valuable, just in different ways. It’s important to know whether you are more in need of descriptive analysis, predictive analysis, or both before you invest in a platform.

For example, it’s great to have a way to generate predictions about future growth, but if you can’t drill down into the underlying data to understand the basis for these predictions or tweak your dashboards to give you exactly the insights you need, you may be limited in your business planning.

See an example:

Growth Share - Marketing Dashboard

Business Analytics — part of Business Intelligence?

Another argument is that BA is simply the user-facing, self-service end of BI — the dashboards and displays.

Or, as Dataversity sums it up:

“Business Analytics refers to the movement of tailoring analytics and BI specifically for non-technical and business users.”

In the past, the hard parts of BI were performed by IT analytics professionals, resulting in static reports. Need a different insight or query? You’d have to put in a request. But the rise of self-service BI means that with the right platform, non-techies can now use front-end tools to generate their own dashboards and manipulate data on demand using “self-service analytics” — or, as some would have it, BA.

Business Intelligence — part of Business Analytics?

Confused yet? Some experts see BA as the whole package: data warehousing, information management, predictive data analytics, reporting, etc. with BI just being one strand of that.

Under this model, BI is still the “descriptive” part of data analysis, but BA means BI, plus the predictive element, plus all the extra bits and pieces that make up the way you handle, interpret and visualize data.

Does any of this matter?

Lastly, there are those who say that the distinction has now become meaningless. There’s no genuine difference between the two — or, if there is, it’s not worth paying attention to.

Industry insiders like SAP’s Timo Elliott point out that the waters have been thoroughly muddied by two things: fast-changing technologies and fancy marketing speak.

Put simply, companies have always needed (and will always need) insights about their business performance for the same core reasons, but the skills, tech, and strategies used to draw out those insights evolve all the time.

When there are overlaps in new software solutions and the functions they provide, it’s harder to say exactly what counts as BI and BA. And, on a more cynical level, vendors often treat these terms as marketing buzzwords rather than worrying about accurate descriptions when plugging a new product.

The right tech matters

If it’s all just semantics, why does this matter? Well, for one reason: at some point, you need to figure out which technologies, tools, and approaches you should invest in to get the insights you need.

We could argue over which definition of BA and BI are most accurate forever, but the real problem here is that different people use them to mean wildly different things.

That means it’s not terribly helpful to frame your purchasing decision as business analytics vs business intelligence. It’s more important to find out what’s really going on under the hood than to get hung up on whether a vendor bills their product as BA or BI.

Focus on what you need the system to do, and who will use it. How detailed do you need your insights to be? How tech-savvy are the people that need to run queries the most? How much control and visibility do you need over the process and the source data itself? Are you more interested in understanding how you got here or getting an idea of where you’ll go next?

Ultimately, these questions will help you establish the level of self-service you need, and whether your data requirements are geared more towards descriptive or predictive analytics, leading your business in the right direction — regardless of what you call it.

BI and Analytics for Data Engineers
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