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Data Analysis is a powerful tool to enable business decision making. It can also be a dangerous way to misunderstand your business, as Mark Twain said, “There are three kinds of lies: lies, damned lies and statistics". The most common failure in data analysis and visualization lies in confirmation bias ; meaning you start with a hypothesis and work to confirm it. In exploratory data analysis, you should always start with a clean slate, work to find structure in your data and then analyze its root cause. This gives you a working hypothesis which you can then work to disprove. If you cannot, then you may have a useful business metric.

Beyond statistics, data mining is an excellent discipline for advanced business analytics with the basic mission of identifying non-intuitive relationships in large data sets. Most businesses stop with simple statistical analysis. Data mining has much more depth and eventual business value. The main disciplines in data mining are Correlation, Aggregation, Clustering , Affinity Grouping and Classification. More on these techniques in future posts.

The careful analysis of data is a business tool that can enable timely and informed business decisions. However, without vigilance the confirmation bias can rob your analytical efforts of meaning and lead you confidently right out of business.