Exploration and analysis. One type of analytics is exploration and analysis. This approach involves navigating historical data in a top-down, deductive manner. To start, an analyst needs to have an idea of what is causing a high-level trend or alert. In other words, the analyst must start with a hypothesis and deduce the cause by exploring the data with ad hoc query tools, OLAP tools, Excel, or SQL. Here, the burden is on the business analyst to sort through large volumes of data and find the needle in the haystack. This type of analytics has been around for a long time and constitutes the bulk of activity done by business analysts.
Prediction and optimization. Another type of analytics is prediction and optimization. Although the algorithms used to power these types of analyses have existed for decades, they have been implemented only by a small number of commercial organizations. Business users model historical data in a bottom-up, inductive manner. They apply data mining tools to create statistical models to identify patterns and trends in the data that can be used to predict the future and optimize business processes. Here, the process is inductive. Rather than starting with a hypothesis, you let the tools discover the trends, patterns, and outliers on your behalf. (However, in reality, it takes some knowledge of the business process and data to apply these tools with reliable accuracy.)