While the infographic below has nothing to do with accounting outright, in many ways it does. I found myself drawn to the simplicity, but also the volumes of information that are hidden behind the chart.
2.8 billion tweets were analyzed- and someone narrowed them down to less than 25 major topics to provide meaningful information about 2017. We could not do this ten years ago, maybe not even five years ago.
Analyzing “big data” is a BIG responsibility, and you can easily get lost in it. The volume of data that systems can digest with today’s technology is increasing at rates we cannot even comprehend.
So, if you want to analyze big data, what does it really mean? I have been practicing public accounting and all the tenets that surround it for many years. For all those years, I have been fascinated with data. I like to make sense of what I am looking at- a better way to say it might be making the numbers mean something.
I spent many years pursuing a method to analyze the data- from simple financials to manufacturing reports to excel spreadsheets. Twenty years ago, was a completely different ballgame than today. In today’s world, there are numerous of methods, software and people that claim they can do this for you. The bottom line is, if you don’t know what you are looking for, you will get lost in big data.
Let’s suggest that someone presented you will all 2.839 billion tweets and told you to analyze it. It’s easy to say NOW that this would be your conclusion, but you must ask yourself many questions before you START to analyze the data such as:
1. Why is this data important to me? It’s difficult to believe, but we often capture data that means nothing to anyone.
2. What information do I want to discover? This leads to the source of your data. More specifically, is it customer information from your CRM, or is it product mix from your sales information?
3. What information has the potential to impact the way I do business?
4. How might “x information” change the decisions I am making every day?
These are broad questions about the data being captured. However, if you are the one who is capturing or analyzing the data, the questions need to be more, well, “geeky”. Some might include:
5. What will it take for me to believe the data results have integrity? This refers to using current, relevant information, or “clean” data.
6. How are you going to analyze the data? Clearly viewing or sorting 2.8 billion tweets would not have resulted in this telling infographic!
7. How should the data be presented? And Who will be viewing it? This is important because people process information in diverse ways. Some understand line charts, some number graphs and some just want you to tell them “X number of people tweeted about healthcare in 2017”.
This is only the tip of the iceberg- it goes very deep, and involves curiosity and communication at many levels. Once you understand that it takes a certain skill set to know what data you need, then you can begin to research the methods, software and people that can be deployed to crunch the data.
Jennifer A. Kinzel, CPA, CMA, MBA
Director, WVC RubixCloud