In many situations, large amounts of data are collected to be studied. For example, economists may receive thousands of survey responses or may look through endless amounts of government and census data on huge segments of the population. Other academics may also receive numerous large bodies of unorganized information; for example, a scientist studying a potential cure for cancer may receive the test results of hundreds, or even thousands or millions, of patients. In business, data may also be collected in the form of sales data, customer receipts, transactions or other types of information.

All of this data provides information and likely contains patterns and trends that can help shape and govern behavior. To use the information, however, the data must be organized, analyzed and understood. Data analytics refers to the process of organizing and analyzing all of that data.

Just as there are many different types and sources for data, there are many different methods of analytics. Some data must be organized manually and hand coded. Other large databases of information can be sifted through using specialized computer programs which make the process of data analytics streamlined and simple.

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