Understanding the Key Differences Between Reporting and Analytics in Business Intelligence (Full Transcript)

Speaker 1: What's the difference between reporting and analytics? These two terms are often used interchangeably to mean the same thing, but they're actually two very different forms of business intelligence and serve very different purposes. For starters, analytics is a much fancier word, so we hear it being thrown around when we actually mean to say reporting. What actually is analytics and how does it work? Reporting is the process of organising data into formal summaries. To make reports less boring to look at, we add some charts and graphs, but the key word here is summary. Analytics on the other hand, is a process of exploring data in order to extract meaningful insights which can be used to better understand and improve a business. So where reports can show you where something might be wrong, analytics can tell you what's Analytics deals with a lot of numbers, so it doesn't always look as pretty as a report, but there's one thing in particular that makes analytics special, and that's data pivoting. Let's look at an example. A standard report is usually something like a graph that plots your sales on an axis. The graph is built from flat data. And that's okay, it's very useful to look at once a month. But if we want to dig deeper to see what these sales are really made of, there's just too much data to deal with. Pivoting a report means transforming your flat data into two dimensions. We simply take all the dates, get all distinct values, and put them onto an axis. Then when we take all your selling channels, group them, and put them on another axis, you end up with a grid. Where each cell is the sum of all the sales that happened on a specific date, on a specific sales channel. Now that we have all this data in a manageable form, we can roll it up. Having the data in this form means we can do some cool calculations. For example, you can work out a growth rate and view it alongside your sales figures. Beyond just pivoting the data, analytics means the data is actually stored and viewed in a multi-dimensional form. The best way to picture it is to think of a cube. You have dimensions that represent how we've grouped your data. Each cell of the cube holds a number that represents a measure of business performance. It could be sales figures, profits, expenses, budgets, or forecasts. When you view this data in the real world, you don't see it in three dimensions, although that would be cool. Instead, we can use clever software to slice a piece of the cube and display it in the form of a grid. Having data in this format gives you limitless possibilities to explore, question patterns, make calculations across multiple dimensions, and drill down into granular data. Whatever you need to do to gain valuable insights into your business to make data-driven decisions.