Data processing methods are a way to turn large amounts of raw data into usable and understandable information, using methods such as batch processing, real-time processing, data mining and statistical processing. Data processing used to be done by hand and took a very long time, but today almost all data processing is done by computers, making the process much quicker.
Whether the state is trying to find patterns in census information, or a business is looking to identify where they are getting most of their sales, large amounts of data always need to be consolidated and analyzed to find usable information. Batch processing is the easiest form of processing, where computers analyze data in large batches at set times. For instance, payroll is batch data, because a computer analyzes all hours at the end of every pay period.
Real-time processing is used for data that can be analyzed immediately. For example, a radar system processes information in real-time, so that the operator gets feedback immediately.
Data mining takes information from multiple sources and tries to combine it and find patterns. For instance, grocery stores look at sales of one item and see if it correlates with another item. If everyone who buys peanut butter also buys jelly, they can put the two items together.
There are many different ways to process data, but in general, computers have completely changed and improved data processing methods. What used to take months or years can now take only a few seconds. Computers are able to take large amounts of raw data and find important, usable information in the trends of that data.