Business Analytics vs Business Intelligence?


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:

  1. 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.
  2. 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…


Did you find this interesting / useful? Think about following me on twitter!

75 comments to “Business Analytics vs Business Intelligence?”
  1. Pingback: Analytics vs Business Intelligence? | Life as a Data Analyst

  2. When Intelligence is derived or Analytic tools are used on non-business data for non-business purpose – on social, government, law purposes – still call it “Business” Intelligence or Analytic…. considering “Business” part as obvious!

  3. Pingback: Is Big Data The New Term For Business Intelligence?Innovation

  4. Love it! I tried to revive Decision Support System a few year ago but I didn’t get very far. I agree with you that it’s a better term in many ways. At least DSS makes the roles of ‘man vs machine’ a bit more clear. I always thought the term BI implied that the ‘man’ just sat back and waited for the ‘machine’ to tell him what to do. I do think ‘analytics’ has evolved in some spheres as shorthand for ‘predictive analytics’ which explains why BI gets relegated to the ‘rear view mirror’ operational BI. But ultimately I agree with you. The terminology shouldn’t matter.

  5. I do think there is a difference between Business Intelligence and Business Analytics. Business Intelligence is a subset in the Business Analytics space, i.e. it is one type of Business Analytics.

    IBM has what they call an Analytics triangle to categorize different types of Business Analytics based on the types of questions the user is trying to answer.

    The base of the triangle is: Descriptive Analytics and answers the questions: What has happened in my business? Why has it happened? What do I know about my customers, competitors, suppliers, etc.? Examples of this are BI, reporting, advanced visualizations etc.

    The middle of the triangle is: Predictive Analytics and answers the questions: What is likely to happen? What is likely to be true about my customers, competitors, suppliers, etc? Examples of this are forecasting, regressions, data mining, most big data applications, simulations, etc.

    The top of the triangle is: Prescriptive Analytics and answers the questions: What should I do? What is the best course of action given what I know and what I think will happen? Examples of this are optimization, mathematical programming (LP, MIP, QP, CP etc), heuristic algorithms etc.

    The reason for the triangle shape is the garbage in – garbage out concept. Without solid descriptive analytics, most predictive models are completely irrelevant, and without solid descriptive and predictive models, most prescriptive models are irrelevant.

    I hope this helps clarify some of the confusion.

    • Daniel — did you read the post? No, it doesn’t help clarify the confusion! The whole point is that I don’t care about IBM’s definition — or anybody else’s — because there are so many different definitions out there, it’s pointless to debate them…

  6. Pingback: Business Analytics vs Business Intelligence? | Business Analytics « Sykes' Blog

    • Igor, IDC does indeed have a taxonomy, in which BI is just part of BA (the other two are EPM/analytic applications, and DW management systems). Gartner also uses “Business Analytics” as the overall term… But that doesn’t really impact what this post is about…

  7. First of all…if new terms confuse the hell out of someone it does not necessarily mean that you can fall back on old terms without any consequence. Even if they mean exactly the same.
    BI stands for the speed in which an organisations can adapt to a changing environment. Changes in the market or new government policies for example.

    In fact, we are talking about strategic management, right?
    We receive signals…
    Collect data from it.
    Interpret information from the data.
    If we are bright we extend our knowledge form this information.
    And we use this knowledge to act upon or innovate for example in order to stay alive (or grow) as an organisation

    From this point of view i understand what you mean but i think terms do matter. BI says a hell of a lot more than BA.

    In fact you prove with your artical that you have difficulties adapting these new terms. This is exactly where BI stands for: “How quickly can you adapt ot new circumstances?”.

    And furthermore what do those graphs tell us? The information it gives to me has really nothing to do with business intelligence? The graphs are very suggestive. Can you really explain what these graphs mean relating to BI or BA as you want to call it. Becaus searching for something does not give more information to me than the fact that someone searches for it. Let alone that i can derive any other knowledge from it.

    Maybe these graphs only show that not every organisation benefits form BI…..

  8. I agree that the terms are misleading and confusing. Remember when it was called “decision support”?

    I think that there is a continuum from reporting to data science (another lovely clear-as-mud term)… with different skill-sets, different staff, and different features/tools used across the range. Remember “knowledge-workers”?

    I do not like the use of the term “analytics” when “reporting” is what is meant. I can tolerate the use of the term “analytics” when “statistics” is what is meant. I hate the use of the term “analytics” when scoring is what is meant. Humans analyze when they direct their attention to evaluate a problem… not when they read a number on a report…

    Lets not confuse the tools or the process with the business objective. Analytics, Business or otherwise, is a process with the aim of acquiring or raising Business Intelligence. Analytics tools and data warehouse data support the process.

    Maybe we should go back to “decision support” and realize that all of this is in support of business decisions?

  9. Timo, We all take a journey… I think you are debating the fact that the “buzz” changes, but often it doesn’t have an effect on busienss… With that said, you are debating incorrectly and in an ineffective way that BI and BA are the same. Renee above points out a good link. BI was a movement focused on assessing business with reports on data we primary held in our 4 walls. BA is an exploratory approach leveraging analytics techniques that have been available for 30+ yrs, but not applied to the business in these ways. BA is about exploring data for alteratives. If its predictive or real-time they are primarily leveraging speed of in-memory systems and linear regression to predict behavor (no different than NASA did on their rockets in the 60’s) When considering difference, you must also add the unprecedented growth in data ( and businesses opening up their inspection of data to new sources outside their control is notably different. BI and BA are not the same, the real question is will Corp’s leverage their opportunity for real value or treat them like new toys and bore with them quickly.

    • Andy, clearly I have been ineffective, in that you’re just repeating exactly the point I was trying to refute. I don’t care what you think the difference between the two terms is – my twenty years in the industry tells me that other people won’t agree with you, and that debating the differences gets in the way of doing actual work. As for the last point: the growth in data has ALWAYS been unprecedented, and always will!

  10. Pingback: What is Big Data ? – another sterile BI debate ? | Antivia Blog

  11. Pingback: When is a Dashboard not a Dashboard ? | Antivia Blog

  12. Sorry Timo, but I’m going to throw another “no” at you:

    Here’s another article that describes the two terms and its relation crystal clear:

    So yes, I’m also of the camp that terminology does matter.

    While I agree that getting things done is more important than how you call it, in the case of Business Intelligence/Business Analytics/Operations Research/Management Science/Data mining/Data science/Industrial Engineering it can be diluting the value of each respective practice if we amalgamate them to be one and the same thing.

    Just like calling it a “car” would whitewash the value/benefit of a SUV vs Hybrid vs Sports car – to the respective audience.

    We need to be specific, and language/terminology just so happen to be our way of making sense of the universe.

    • Yes, the tools you’re using should have different names, just like hammers and spanners. But the instant that people start talking about something being a “hammer problem” or a “spanner problem”, they’re asking for trouble, because you’ll probably need both, and you’re concentrating on the tools, not the problem. Any clearer?

  13. Pingback: The Business Intelligence Pipeline: Are you making the most out of BI?

  14. Pingback: Bizintelligence Forum » Analytics V/s Intelligence

  15. I agree we need to get on with job regardless of what name fashion has given it today. Its absurd, so much discussion on topic is fraught with debate about nomenclature that threatens to overtake the job itself. Prob what set Timo off on his post. Thanks Timo for that. Very timely.

    But I agree also with Matthew Okane comments reminding us of the ‘business user’. Given his stature maybe Timo is dealing with a rarefied strata of very knowledgeable people who can deal with the ambiguity in nomenclature and get on with job.

    In my experience though the ‘common person’ you work with at a job site is at best vaguely aware of BI or analytics. They may want to get on with the job if they only knew what tools and processes to use (Timo’s #1 & #2 above). This is not just a BI/BA issue, IT concepts in general such as ‘database’, ‘programming’, ‘queries’, etc are practically as inaccessible as heart surgery for most non-technical people. Although BI or analytics are great ‘hooks’ or motivators to make these other things more accessible .. but i digress.

    So, it does matter what you call things. We use words to communicate. People need words to articulate, research, understand, learn, make plans, assign budgets. We need to use words that everyone can understand, not jargon and marketing speak. Personally, I think “reporting” is the probably the most ubiquitously understood and useful categorization for the entire space.

    There is such enormous value waiting to be unlocked by using information technology better. Its ironic that technical jargon and marketing branding seem to be eternal impediments to realizing this value.

  16. But the ‘business users’ in my example do need to differentiate. If a company needs to answer the ‘Why’ questions we need to be educating them that traditional BI won’t fully meet their requirements. Whether you want to call it analytics, data mining, predictive modelling, Peter or anything else it doesn’t matter as long as you can sufficiently distinguish between technology used to report and technology used to ‘ask’. I agree that maybe as an industry we haven’t fully defined those boundaries under single terms but we must have a decent elevator pitch for both, which I think Renee’s link does a good job of doing.

    Perhaps we need to draw the line between data-driven analysis (predictive modelling, unsupervised learning) and human-driven analysis (reporting / MI).

  17. Timo – I must repeat that word back to you – “No!”

    The reason why people need to distinguish analytics and reporting / business intelligence is because vendors are attempting to muddle it up in the first place. Renee’s link is a perfectly sensible way of distinguishing between the functionality required to answer these business questions.

    Traditional BI tools cannot answer the questions under Business Analytics – organisations need tools like R, SAS, SPPS etc. with sufficient data mining / predictive functionality to help them. If you want this backed up just ask any analyst in a credit risk function in a bank and ask them whether they use a BI tool or an analytics tool to build their credit risk models.

    • Sorry Matthew, I’m still not buying it… yes, you sometimes need to talk about the technology, but it’s not the “vendors fault” that the term analytics is ambiguous, and best avoided. Much better to stick to other more technical terms, exactly as you have done in your comment: if you need advanced statistical algorithms in order to solve a business problem and you have to talk about it to the business people, then “predictive” and “data mining” are better terms to use (except our recent research shows that business people talk about “data mining” in a very general sense, too, so maybe not). But I don’t think business people really care, as long as it does the job. Call it “Peter” if you like… (“for that business problem, you need Peter, he’s expensive!” “Oh, OK…”)

  18. Pingback: to read or to write? – that is the question « Data Visualization

  19. Pingback: What I Found Interesting About Gartner BI Summit 2012 London | Innovation

  20. Pingback: What I Found Interesting About Gartner BI Summit 2012 London | Business Analytics

  21. Me too, have over 20 years in the market. Have seen this. First we have reporting, then we had dw, then comes dw studio (reporting and DW). Soon reporting changed to be BI, just name change, and there we go. Now it is here again, BI is BA, shout loud!

  22. This is an excellent information about business intelligence. Where you put Google Analytics in business intelligence sectors? I think Google analytics is also based on concept of business intelligence.

    Tell me your opinion?

    Pratik Joshi

  23. Pingback: Business Analytics vs Business Intelligence? | Accounting and Small Business /Beverly Shares

  24. Hi, Timo. It doesn’t matter if we call it business intelligence or business analytics, the purpose of both is to make businesses more agile and business information actionable. Today, businesses are well versed with the fact that a lot has changed since Business Intelligence first came into scene. I read an interesting blog that, like your post, throws light on BI concept and is of great interest for business executives. It explains -why traditional BI tools fail in today’s world and why businesses are opting for packaged BI solutions. Read on from

  25. Timo,
    I would like to build on the business side of the equation – the need for information (whatever you call it).

    1. It is not sufficient to provide analysis and data. You have to provide useful information that is readily digested and understood. The newer generation has very little patience so they have to be able to obtain answers to their questions without a lot of sifting through the data. So, the ability to present the data as information (whether via charts, alerts, or other means) is just as important as being able to get the data
    2. Often, the real value is in obtaining answers to the second or third question users ask. What I mean is that a report or set of analytics usually creates more questions than it answers. The value is being able to answer that question, and perhaps another layer or two of questions after that.
    3. This is a global world, and managers and executives need to be able to obtain information. ask supplementary questions, and obtain answers – wherever in the world they are. So mobile is critical
    4. Business is speeding up. Decisions have to be made quickly if opportunities are to be realized. So, analytics have to be made with speed – and they have to be performed with masses of data, both structured and unstructured. There is little value in analytics that help you see the mistake you just made (because you lacked information and insight).

  26. Timo,

    Good article, though in regards to your “No!” response to Renee, I believe the context and scope of a particular organization or department(s) must be considered. While I do agree with most of what you’ve stated here after over a decade in the industry (private sector, public sector, consulting), what is considered “BI” vs. “analytics” can differ widely between organizations. In those organizations where BI and analytics are defined and performed by separate groups (who are likely very collaborative), the link Renee provides may lay it out quite well from a functional perspective. I’ve certainly seen a number of organizations who have separate BI teams (often within IT) and Analytics teams, either dispersed across business units, or centralized under a particular business unit external of IT. This can work, and it can work quite well.

    Stating BI and BA cannot be uniquely defined is also a bit misleading. Everything must be put in context – there is no “single version of the truth” here.

    • I just reread the article Renee referred to, and I guess I have to say an even louder “no!”.

      There may well be two teams that use different technology, and with different levels of sophistication about how they use data, but I would continue to say that the way the article attempts to separate BI and analytics obscures rather than helps.

      I suspect that the teams you’re talking about are separating the teams running (most of) the technology stack (in IT) from the teams that are interpreting that data (in the business, with some extra technology on top that doesn’t require connections to other IT systems).

      I don’t think calling these two teams “BI” and “Analytics” is useful. In particular, in this case the “Analytics” team would actually asking all the business questions that the “BI” column in the article (i.e. “what happened, when, how many”), while the “BI” team would be an internal technology service provider. And if I’m wrong, and the “BI” team does really answer the business questions, then I don’t believe it should be a separate team from the “Analytics” group….

  27. Pingback: Business Analytics vs Business Intelligence?

  28. Pingback: Confluence: Abiliton SaaS

    • Renee,

      No! That’s exactly why I wrote this post — these definitions fall exactly into the trap I’ve talked about in this post: “what happened?” and “why did it happen?” are different BUSINESS questions, but answering them requires a spectrum of technology, that just doesn’t split into neat little bundles with agreed-on names….

  29. Pingback: Whistling Past the Brand Graveyard with BusinessObjects

  30. Pingback: SAP Business Analytics in Portugal | Business Analytics

  31. Timo – Good article however your Google Trends’ charts are misleading. The reason “business intelligence” search trend is downward is because more people search for “BI” rather than “business intelligence”. I would have included that chart as well.

  32. Pingback: Analytics V/s Intelligence « Forum for Business Intelligence Professionals

  33. Who knew Business Intelligence knows that it’s strictly business oriented. Marketing and branding have their rules… So now it’s time to say that it’s about Business Analytics… more or less….
    Concept and business decision process we would support and let customers drive better are not so different.
    Turn data into actionable informative assets to take better decisions is the key of BI. And is still the key of BusinessAnalytics 🙂

  34. Timo, great article. Business Intelligence is much more than software. BI is a reliable, analytical process that transforms raw data into relevant, accurate and useable strategic knowledge. The key is to utilize the powerful BI applications available today to automate this process, in order to make sound decisions fast, aiming to the sustainable profitability of the company.

    I think this process is always analytical whether you use a primitive or basic static reporting tool or the most sophisticated statistical or predictive software.

    Regards, Bill

  35. What about industrial espionage as a subtopic of business intelligence? Just because we are a bunch of techies doesn’t mean there aren’t other ways to gather and use decision-relevant information. I can’t see this subtopic fitting into business analytics…

    • Thanks for pointing out another meaning of “business intelligence” — a bit orthogonal to this one, although ultimately, it comes down to information to run your business…

  36. Pingback: What’s The Difference Between Business Intelligence & Business Analytics? «

  37. Pingback: What’s The Difference Between Business Intelligence & Business Analytics? - Ahmed Lashin

  38. Is is only me who is shocked by that consistent drop every December in trending for BI in Google trends?

    Note the consistent spike every first quarter as well.

  39. I do not agree that business intelligence (BI) and business analytics (BA) are blurred concepts or terms — however, I do agree that these terms have become blurred in the decision analytics lexicon — so be it — what is more important is that we grasp what is required for good BI/BA processes and solutions — more about the qualities of the successful BI/BA analyst (and other links) here:

    Thank you for the opportunity to comment…

  40. Hi Timo,
    I agree with you it dosen’t matter what you call it Business Intelligence or Business Analytics, its all about how it can help businesses make better decisions. Being an SAP BusinessObjects customer when we talk about BI we talk about EIM, we talk about crystal reports/webintelligence and dashboards. All of these we consider as tools which are part of the broader BusinessIntelligence framework/infrstructure one has. I had once somebody coming up to me and asking me, is SPSS different from BI and this is what i told them. SPSS is a Predictive Analysis tool which helps organization make better decisions and hence it is a BI tool. As you said different vendors use different names but the core concept remains the same, hence it dosen’t matter what you call it.

  41. Boo loudly? Really? 🙂

    Great post though, Timo. One of the things we’ve found with the use of the two terms is that the BI users (the business side) do trend more towards the term business analytics because that’s been getting more traction in mainstream/business media; and actually, when we did a survey of both BI and business people, the most popular definition for the analysis of business informationto support better decision making and improve business results was “reporting”, not BI or business analtyics.

    I actually just uploaded a video clip of our company’s president talking about the difference between the terms — where we view analytics (i.e. advanced/predictive) as a subset of BI.

Comments are closed.