Let’s Explain Business Intelligence
This is the transcript of a Webinar hosted by InetSoft on the topic of "An Explanation of Business Intelligence." The speaker is Abhishek Gupta, product manager at InetSoft.
Today’s topic, to explain business intelligence, is a tricky one. I struggle with the answer to this not because I don't know the answer, but rather because the answer is so different to so many different people. There is not just one definition of ‘What is business intelligence?’ Business intelligence is a massive term. It encompasses lots of different areas, and inevitably my definition is going to be different from someone else's.
If you line up a hundred different consultants that are in the data warehousing industry, and you ask them to define business intelligence you're going to probably get some variant to about 50 to 75 answers. So I'm going to give you my view of it, but please understand this is one man's opinion. That doesn't make me right. It means that this is close, okay, but it doesn't mean that mine is the only version of ‘What is business intelligence’ that's out there, okay.
So I just wanted to lead with that. All right so, business intelligence, this is the hot buzzword really for about the last four to five years, and it's only getting hotter. Data warehousing, business intelligence those are the hot markets to enter right now in the job market.
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Business Intelligence: The Last Frontier
If I was starting a brand-new company I'd certainly be taking a close look at something with business intelligence or something with data warehousing because that's just where the world is moving. It’s like, at this point, the last frontier of what has not really been developed. By the time you watch this who knows, there could be some other new technology. I don't know.
Here's my explanation of BI. It's about getting the right information into the right people’s hands in a format that allows them to quickly understand the data. Now that's a rather pithy statement, and again my definition is just man's opinion of what business intelligence is. So it doesn't make it right. Okay. This is what I think it is.
This is what the webinar is predicated on, if you will. Now to me business intelligence is not just about decision support. It's not just about the making of the decisions here. It's not a methodology that describes the way to go from having no business intelligence and having a lot of business intelligence. There are no step-by-step instructions to have business intelligence.
It's not a methodology here. It's not just about reporting services. It’s not just about Crystal Reports. It's not just about Excel or the tools that we use to make these decisions. Here is maybe an epiphany for you. This isn’t SQL Server Analysis Services. That is not business intelligence. It doesn't make any sense once you understand what business intelligence is and does and is about. You don't have to have a data warehouse to do business intelligence.
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Understanding Data Marts and Data Warehouses
If you don't know what data marts are, or what a data warehouse is, that’s what I am here to help you with. We’ll cover that ground in couple of other webinars upcoming. I would be remiss if I didn't include definitions from other people. The Wikipedia one that I saw says, “BI refers to the skills, processes, technologies, applications and practices used to support decision making”. I like that one. I think that's a rather very compact way to say that.
The only thing that it's missing right there is making sure that the data that you get to the end-user is in a format that they can understand quickly. Sometimes business intelligence fails at the usability end of the spectrum. Some of you who have been in BI will completely understand that. You know there are a couple of other ones, and I realize you can read, so if you have the PDF of this video you can pull these up and read these here.
But I noticed a couple of things here. BI is a broad category, blah-blah-blah-blah. BI is an umbrella term, blah-blah-blah. Okay. So there's a lot of different ways that we can talk about what business intelligence is. And just because the guys at TechTarget or Wikipedia say it's this one thing, that's their opinion. That's their way of treating it, just like this is my opinion, my way of treating it.
Does Business Intelligence Mean the Same Thing as It Did 20 Years Ago?
Twenty years ago, Business Intelligence (BI) largely referred to a set of tools and processes focused on reporting historical data, typically extracted from transactional systems, transformed in a data warehouse, and then delivered to executives and analysts in static reports. The technology stack was heavily IT-driven, with long development cycles, formal requirements gathering, and limited flexibility for end users. At the time, BI was seen as a structured, centralized discipline where data access and analysis were tightly controlled to ensure accuracy and consistency, but at the expense of speed and adaptability.
Today, the concept of BI has expanded well beyond its original definition. Modern BI is interactive, real-time, and democratized, giving frontline employees as well as executives the ability to explore data on their own through self-service tools. Advances in cloud computing, mobile technology, and AI have shifted BI from being purely descriptive to including predictive and prescriptive analytics. Instead of waiting days or weeks for static reports, users can now receive instant visual insights, drill down into the data, and even get automated recommendations for action, often embedded directly into operational workflows.
In essence, while the core objective of BI — turning data into actionable insights — remains unchanged, the way it is achieved has transformed dramatically. The emphasis has shifted from centralized control to agile empowerment, from historical reporting to proactive decision-making, and from IT-managed delivery to business-driven exploration. BI is no longer a back-office function but a pervasive capability integrated into day-to-day operations, strategy, and customer engagement, making it a fundamentally broader and more dynamic concept than it was two decades ago.