Business intelligence (BI) sounds like the kind of thing you’re supposed to pick up in an MBA program — something along the lines of management skills or accounting savvy. In today’s tech parlance, however, it’s actually an umbrella term, one that refers to the various infrastructures, tools and practices that allow you to access and analyze data to improve future business decisions.
It’s a pretty simple definition, but here’s my problem: It doesn’t tell you anything about what BI actually looks like. What are these infrastructures and tools? Where is your data stored and how do you access it? And how exactly are you supposed to use it to bolster your decision-making skills?
In this post, my goal is to illustrate the basic process of business intelligence. Before you can decide whether BI will be a worthwhile investment for your company, after all, you’ll need to know a little bit more about how it works.
Business intelligence starts with data (duh).
Okay, so we’ve established that BI is all about accessing and analyzing data. That data can come from a lot of places: CRM and ERP platforms, CSV files, Excel spreadsheets, web pages and web analytics, social media channels, emails and mailing lists, accounting softwares, etc.
Take a look at those sources and you’ll see that data can also come in many formats. On the one hand, there’s structured data: “The information that fits in an Excel spreadsheet. Its properties and categories are easily filtered in a database.” And on the other, there’s unstructured data: “Data normally written out in a natural language, typed by a person and not formulated for neat databases.”
In many businesses, all these disparate data sources exist separately. The goal of BI is to bring them together.
The next step? Making your data searchable.
Once you’ve identified all the places your valuable data might be stored, you need a way to access it all at once. The first option is to move the data to a single location. You can do this via a process known as Extract, Transform and Load (or ETL). ETL enables you to extract data from different sources, transform it to match the target system’s required formatting, and load it into your desired storage location (known as a data warehouse). Think of it like this: When you use your computer’s operating system to search for a particular document, your results will only reflect what’s on your hard drive. If you want to search all your data, you’ll need to load any documents you’re storing externally onto your computer’s main drive.
Another choice is Hadoop (which, let’s be honest, is really fun to say). Hadoop is an open-source framework that “allows for the distributed processing of large data sets across clusters of computers using simple programming models.” In other words, Hadoop allows you to find data spread across multiple servers with a single search. Instead of putting all your data in one place, you’re using a system that can search it out across many locations.
Some argue that data warehousing and Hadoop are competing strategies, while others suggest that they’re complementary aspects of a broader BI and big data ecosystem. In either case, the consensus seems to be that data warehouses are better suited to handle structured data, while Hadoop was purpose-built to tackle semistructured and unstructured data.
Finally, you need a tool to make sense of everything.
Okay, now you’ve got a way to sort through all your data. However, unless you’re a data scientist, you probably don’t know what to do with it. That’s why business intelligence and business analytics softwares exist.
These softwares are designed to mine and analyze your newly connected data to discover connections, patterns, anomalies, etc. and present them in an easy-to-understand way, often via dashboards and data visualizations. It’s these digestible insights that you, as a business leader, can finally use to make better decisions. And if you’re able to make better decisions on a consistent basis, your organization will be better primed for success.
That’s the 10,000 foot view. Here’s how to zoom in.
Hopefully now you feel like you’ve got a solid conceptual understanding of what business intelligence is and how it works. If that’s the case, start thinking more about your data and how you might use BI in your company. Once you have a clearer idea of what you’d like to accomplish, you can start pursuing different platforms. Some options include Microsoft Power BI, Tableau and Einstein Analytics from Salesforce.