Going back to our previous definition of descriptive analytics, it is used to answer questions about what has happened in a business. It is primary use is to look at the current business situation with an eye towards looking for cause and effect. It helps one to understand how to manage in the present based on what happened in the past.
The vast majority that have attended my trainings on analytics, are looking for help with descriptive analytics challenges. Using unstructured big data for predictive analytics modeling is not really something they are concerned with.
I have found that people who are really engaged with analytics are very driven to self-educate. They are driven by curiosity to make use of cutting edge stuff to tackle bigger and bigger challenges. For data scientists and really good analysts, descriptive analytics is easy and kinda boring.
But that is a small percentage of people who use analytics every day. To most of my attendees, its more about how to cut down on the time it takes for them to prepare the reports they have to make and how to make them more useful to their bosses. That’s where most of my descriptive analytics training has an impact.
How to make a better report? How to build and maintain a simple business dashboard? How to have more impactful power point slides. How to streamline the reporting process? This is one way to look at descriptive analytics… its not just taking historical data and using it for reports, but also how to make the reports better.
So how can we use descriptive analytics? Well, we probably already are. Inventory control, payroll, performance management, quality assurance, sales reports, marketing results… all use forms of descriptive analytics. They take what happen, they look at it and then they make decisions.
For the most part this can and is done in Excel. If you want to supercharge what you do in Excel, then you can use a business intelligence tool to build dashboards and publish dynamic reports. This is where most people doing reports need help. How to better visualize the data so it has more power and how to use BI tools to do things faster than can be done in Excel.
In many, many companies a lot of time and energy has been devoted to building reporting tools in house. And this is generally the problem. The reports are static and hard to change. If you are in a company like this, then descriptive analytics can be a bear.
To make the most of it, I suggest using free tools like Tableau Public, which is free, to demonstrate new ways to analyze and report data, to get the boss interested in updating the way you company reports.
Another big challenge facing analysts doing mostly descriptive analytics in the form of reporting, is blending data. Taking data from different data sources and combining them. This can often be very manual and general done in excel if you company hasn’t invested in a way to centrally store enterprise wide data and make it easily accessible. There are some applications out there that can help you with this, Alteryx and Qlikview being ones I have used and they both have a free demo.
If you are already doing predictive analytics, then you probably have your descriptive analytics figured out.
So, if you need help super charging your reporting, are looking to get started using business intelligence and data blending tools, and/or need to build a business case to invest more into analytics, let me know. I’m happy to help you come up with a much better way to build reports that have real impact and don’t take up all your time.