What’s the difference between Business Analytics and Business Intelligence? The correct answer is: everybody has an opinion, but nobody knows, and you shouldn’t care.
Having worked in the industry over twenty years, I can confidently say that everybody has a different notion of what ANY particular term associated with analytics means.
For example, some people use “business analytics” instead of “business intelligence” an umbrella term including data warehousing, business intelligence, enterprise information management, enterprise performance management, analytic applications, and governance, risk, and compliance.
But other vendors use “business analytics” to indicate some level of vertical/horizontal domain knowledge tied with statistical or predictive analytics.
At the end of the day, there are two things worth differentiating:
- The first is the business aspect of BI — the need to get the most value out of information. This need hasn’t really changed in over fifty years (although the increasing complexity of the world economy means it’s ever harder to deliver). And the majority of real issues that stop us from getting value out of information (information culture, politics, lack of analytic competence, etc.) haven’t changed in decades either.
- The second is the IT aspect of BI — what technology is used to help provide the business need. This obviously does change over time — sometimes radically.
The problems in nomenclature typically arise because “business intelligence” is commonly used to refer both of these, according to the context, thus confusing the heck out of everyone.
In particular, as the IT infrastructure inevitably changes over time, analysts and vendors (especially new entrants) become uncomfortable with what increasingly strikes them as a “dated” term, and want to change it for a newer term that they think will differentiate their coverage/products (when I joined the industry, it was called “decision support systems” – which I still think is a better term in many ways).
When people introduce a new term, they inevitably (and deliberately, cynically?) dismiss the old one as “just technology driven” and “backward looking”, while the new term is “business oriented” and “actionable”. This is complete rubbish, and I encourage you to call pundits and vendors out on this blatant falsehood whenever you hear them say it.
The very first use of what we now mostly call business intelligence was in 1951, as far as I can tell, with the advent of the first commercial computer ever, dubbed LEO for Lyons Electronic Office, powered by over 6,000 vacuum tubes. And it was already about “meeting business needs through actionable information”, in this case deciding the number of cakes and sandwiches to make for the next day, based on the previous demand in J. Lyons Co. tea shops in the UK.
And It most emphatically was not “only IT” or “only looking in the rear-view mirror” as some people pompously try to dismiss “old-style BI”.
At the end of the day, nobody important cares what this stuff is called. If you’re in charge of a project, what matters is working out the best way to leverage the information opportunity in your organization, and putting in place appropriate technology to meet that business need — and you can call that process whatever you like: it won’t make any difference…
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Comments
75 responses to “Business Analytics vs Business Intelligence?”
[…] Elliott wrote, earlier this month, a post about the differences between Business Intelligence & Business Analytics. Post which I think is […]
IMHO…(and so it begins my opinion).
I think we have to look at it the way it is.
Everything begins with the question:
I want to know this..whatever this is.
we can refine the information up to a point. After that point…it is Vegas Baby!!!
call it this or that. All you want is an answer to your question.
Business Analytics already existed at the time of construction of the pyramids in Egypt.
Business Intelligence Howard Drezner introduced with the support of Gartner.
That is why Business Intelligence is part of Business Analytics
That is why Business Intelligence is part of IDC Business Analytics Software Taxonomy 🙂
See also http://eztuir.ztu.edu.ua/1970/1/14.pdf. Sorry, the article in Ukrainian.
I believe there is a lot of difference between the two terms in the logical sense. But they are used as a synonym for each other in the business world, because of the important fact “Business analytical and Business Intelligence are not mutually exclusive”. At any point of time in business, if there is an opportunity for business analytical, then business intelligence is used as the source for analysis. This is another good reason why the terms are used vice versa.
Only if your system has acquired intelligence, it will have the capability to do reasoning and analysis. So the basis for business analysis is business intelligence. Organizations should leverage the power of business intelligence by acquiring quality business data form its customers.
Leveraging Denial’s here…
Descriptive Analysis is used as the base to build the learning into the system and make the system intelligent by gaining quality data along with its patterns.
Predictive analysis is used to do reasoning and analysis on the behavior of the web user/online customer
Prescriptive Analysis is used to make the system, an intelligent, well informed marketing executive who will interactively provide suggestions and solutions for the customer based on their choice.
Agnes,
You have come up with yet another definition for the terms, thus further underlining the whole point of the post: that nobody agrees what they mean, so (a) it’s not particularly useful to push your definition, since it’s impossible for it to be “right” and (b) any attempt at using them in a precise way is therefor best avoided, and the terms should only be used as wide synonyms for each other…
Regards,
Timo
Very late to the post but just stumbled upon and was compelled to chime in. I completely agree with your assessment, Timo. Unfortunately for most of us, at the end of the day we are at the whim of the software vendors who are primarily driving all the information out there on the subject – they will ALWAYS rebrand the idea to sell a new version of the product.
I also agree DSS was much more appropriate and to Ron B’s comment – we called that AI years ago. So the info is either to support the decision of someone or draw the conclusion for them….and then there’s all the unavoidable gray area 🙂
Thanks everyone for the great discussion!
[…] Timo Elliot puts […]
Good post, I totally agree, many new terms are just adding confusion on the market. BI had always include the “predictive” aspect but was rarely delivered because technology (data mining tools, presictive models) was too complex for business analysts.
We could have the same debate around the “data scientist” title, which is nothing else than what we called our “power users” in the past…
[…] Don’t get me wrong. I make a living out of cloud-based software. And I am a serious proponent of business-driven technology and CMTOs, but I also worry about the consequences of excessive hype, experienced too many times before. In fact, I should now quote SAP’s Timo Elliot (check out his post on Business Analytics vs. Business Intelligence): […]
LOL, love your first para and the way it tells it like it is!
I’d suggest the project manager defines any local differences in meaning in relation to the project being worked on and its local context, and then move on.
Any discussion of BI vs. BA should begin with “IMHO..”. In my humble opinion, (or at least the way in which I have internalized it) is this: There is a perceived difference between the two – that being the degree to which historical data, predictive insights, and the optimization of constraints are processed for consumption. Analogy. A bowl of loose leave fresh spinach with an egg in it is a salad (BI/Anaytics?). A scrambled egg with spinach in it is an omelette (Analytics/BI?). In any case, your meal is served to you (Reporting). Same ingredients but a very large perceived difference to the consumer.The consumer’s decision to “for here or to go?” is Optimization. So, IMHO, your meal is data, how it is prepared and delivered (reported) is Business Intelligence. Letting the consumer know that his train is leaving in 10 minutes (something not related to his meal) and he should get his meal to go is Analytics (optimization). Thus, IMHO, BI is subject matter expert driven. Analytics is data driven. BI gives consumers what they asked for. Analytics is giving the consumer information that is derived from seemingly unrelated sources (a recipe and a train schedule) that puts BI in an unexpected derived context.the value of which is greater than BI by itself.
While I do agree with the author (Timo Elliott), it was nice learning what Daniel had to day about the interesting triangle. Well, does this clarify the confusion? Yes, in a way to a point that Daniel mentioned, and no (at a higher level) as we keep shooting up these cool new terms into IT jar-gun taking away focus from the real purpose it was meant for – to help support informed biz decisions. So, yes, I do agree with Timo. No need of any emotional debates! 🙂
@Tobias Nittel (I am your fan the way you put it) and Dezhan Pi (as far as the relevance of this post is considered): Couldn’t agree more with you guys.
Great post! Even though it was written 2 years ago, it still seems quite relevant. (The world didn’t change that fast.) The new entrant that helped market the term “business analytics” seems to be IBM, as shown from google trend. Obviously, there is really no much difference.
Let’s step back a little from being tempted to takes sides in that emotional discussion.
Objectively, it is not important how we call it – the ‘user’ will elect the term that he thinks fits best to what he is trying to do.
To that extent he will choose to call everything an analysis of data, whether it is a simple query or a complex statistical model. We have offered a new buzzword and we can’t expect the audience to draw clear lines the way our marketing departments would want the world to behave.
Whatever one positions needs to be put into context of the benefit that is offered. Being precise helps to evolve from hijacking category labels. When will we learn to listen to what a customer wants to do rather than clubbing him with our newest cool term.
The next thing we are going to argue about, is whether my Big Data really is big enough. Someone recently pointed out that the ‘Cloud’ used to be a symbol of uncertainty and blurriness in diagrams and we have turned it into meaning flexibility. It’s all just semantics.
I agree everybody has an opinion and it shouldn’t matter. However I can’t say we shouldn’t care. The public opinion is overwhelmingly shifting in favor of analytics and BI is losing out. I think analytics became the more fashionable word around the same time that vendors felt the market was mature enough for their sophisticated products. I will go one step ahead and say vendors played a major role in the term gaining importance. I see the same thing happening with Big Data now. How is what has happened in the last 5 years to data so different from what it was 5 year prior? Why is data so Big now? I have penned my thoughts here:
http://gazalkapoor.wordpress.com/2013/03/22/business-intelligence-vs-analytics/
Gazal, I completely agree that Analytics is becoming more fashionable, but I’m afraid your post is example of the ridiculous assertions that drove me to write this screed in the first place. To repeat, ad nauseam: BI was/is absolutely about “actionable information” and it is a waste of time to claim that “analytics” is different…