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Data Processing to gain information

So much raw data is being collected constantly in all fields. Every purchase you make, those you return, websites you visit—all involve data that businesses collect. But what does it mean? Computers enable us to process data to turn it into information for decision making and research. Computers can often identify patterns in data that individuals would not be able to detect. As is often the case, there are also trade-offs to consider with large amounts of data.

Data collected from all types of events—including visits, searches, inquiries, orders, returns, temperatures, scores, attendees, acres planted, acres lost, acres harvested, fish, birds, photos, videos, and audio files are considered to be raw data. These are all just values and descriptions until we make sense of it. While humans can usually do an adequate job on small amounts of data, there is no way we could process the vast amounts of data now collected in many raw data sets. We get tired, distracted, and bored, and then errors occur or opportunities are missed.

How Computers Help Process Data


One area computers are very helpful with is “cleaning” the data. This includes removing corrupt data, removing or repairing incomplete data, and verifying ranges or dates among other steps. Removing or flagging invalid data is very useful. Again, individuals could easily miss errors in the data, which could cause incorrect results in later processing.


Computers are also able to easily “filter” data. This means different subsets can be identified and extracted to help people make meaning of the data. For example, all temperature values greater than 98.6 could be meaningful and need further processing or perhaps just a count of how many there are in the entire data set.


Additionally, computers can help make meaning of large data sets by grouping data with common features and values. These groupings or classifications would be based on criteria provided by people who need to work with the data. There could be single or multiple criteria used for these groupings. It would depend on the reason that the data was collected.


Computers are able to identify patterns in data that people are either unable to recognize or cannot process enough data to see the pattern. This process is known as “data mining.” New discoveries and understandings are often made this way. When new or unexpected patterns emerge, the data has been transformed into information for people to begin to interpret. Computers make processing huge amounts of data possible so people can make sense of it.

Machine learning is related to data mining, but it uses the data to make predictions. Through these predictions, actions can be programmed to occur when certain criteria are met, making it appear the device has “learned” how to react or perform.

How People Work with Computers to Process Data


Collaboration is a technique especially useful in working to analyze data. Having a group with different backgrounds, specialties, cultures, and perspectives can result in better analysis and use of the data. Someone may ask or notice something that others with similar backgrounds or someone working alone would not. This could lead to a new hypothesis or discovery about what the data represents.

The use of technology now makes collaboration much easier. Remember that the Web was created to allow scientists across the globe to share documents for collaboration. The tools are continually improving, allowing people in different time zones and locations to easily work together. Collaboration in a face-to-face environment is always beneficial, but technology provides the opportunity for many to collaborate via live-streaming and video-conferencing tools. It also provides a way for multiple people to work together on a shared document or presentation, but in their own time zone and on their own schedule.

Sharing and Communicating Information

There are many tools available to aid in communicating to others the insights identified from the data. Graphics in the form of charts, tables, and other designs are useful to present data in a visual format and in summary format. Remember the phrase, “A picture paints a thousand words”? Use it. The human brain is wired to process information visually, so the use of images and other visual tools are effective ways to get a message across to help others understand it. Providing ways for others to interact with the data, such as providing sound files or videos when someone selects an option is also useful.

Published on Mon 04 August 2014 by Dale Hampton in Computer Science with tag(s): education