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Data Processing
Data processing occurs when data is collected and restated into usable information. generally performed by a data scientist or platoon of data scientists, it’s important for data processing to tighten rightly so as not to negatively affect the end product or data affair.
It starts with data in its raw form and converts it into a further readable format. Giving it the form and atmosphere necessary to be interpreted by computers and exercised by workers throughout an association.
All About the Data Processing Cycle
The data processing cycle consists of a series of ways where raw data(input) is fed into a system to produce practicable perceptivity(affair). Each step is taken in a specific order, but the entire process is repeated in a cyclic manner. The first data processing cycle’s affair can be stored and fed as the input for the coming cycle, as the illustration below shows us.
Six stages of data processing
Data collection
Collecting data is the first step in the data processing. Data is pulled from available sources, including data lakes and data storage. It’s important that the data sources available are secure and well-erected so the data collected (and latterly used as information) is of the loftiest possible quality.
Data medication
Once the data is collected, it also enters the data medication stage. Data medication, frequently appertained to as “pre-processing” is the stage at which raw data is gutted up and organized for the ensuing stage of data processing. During medication, raw data is diligently checked for any crimes. The purpose of this step is to exclude bad data (spare, deficient, or incorrect data) and begin to produce high-quality data for the stylish
Data input
The clean data also entered into its destination. And restated into a language that it can understand. Data input is the first stage in which raw data begins to take the form of usable information.
Processing
During this stage, the data inputted to the computer. In the former stage actually reused for interpretation. Processing done using machine literacy algorithms. Though the process itself may vary slightly depending on the source of data being reused (data lakes, social networks, connected bias, etc.) and its intended use.
Data affairs/ interpretation
The affair/ interpretation stage is the stage at which data is eventually usable to-data scientists. Online videos, images, plain textbooks, etc.). Members of the company or institution can now begin to tone-serve the data for their own data analytics systems.
Data storehouse
The final stage of its processing is the storehouse. After all the data reused stored for unborn use. While some information may put to use incontinently, much of it will later serve a purpose. Plus, duly stored data is a necessity for compliance with data protection legislation like GDPR.
The future of data processing
The future of this lies in the pall. pall technology builds on the convenience of current electronic styles and accelerates its speed and effectiveness. Faster, higher-quality data means more data for each organization to utilize and more valuable insights to extract.
Conclusion
All these computer systems remain interconnected with a high-speed communication network. This facilitates communication between computers. However, the central computer system maintains the master database and monitors it accordingly.
