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Data Processing Cycle | Definition, Stages, Use & Examples

All the virtual world is a form of data which is continuously being processed. Data Processing Cycle is term used to explain the sequence of steps or process used to process the raw data and turn it into readable form and generate meaningful information. The growth of various sectors depends on the availability of data, processing and reliability of data sources. This continuous use and processing of data follow a cycle. This might provide results instantaneously or take time depending upon the need of processing data. The complexity in the field of data processing is increasing which is creating a need for advanced techniques. Big Data is another big push in this field. All the companies are coming under one roof for data mining, data management and processing it and making their services better or reaping more profits and further analysis.

Data is being processed at increasing level so as to obtain desired results. The processing of data is done in real time by various companies by applying various logical operations, doing financial calculations, data validation, transaction processing etc. This processing work is majorly done by electronic data processing. Such automated processing and use of computer systems takes care of collected data, processing work, big data, processing operations, data output etc. Use of artificial intelligence is also gaining popularity as it helps in more effective management of data.

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What is a Data Processing Cycle?

Data processing cycle as the term suggests a sequence of steps or operations for processing data i.e., processing raw data to the usable and readable form. The processing of data can be done by number of data processing methods and processing systems.

Stages of data processing: 

  1. Input – The raw data after collection needs to be fed in the cycle for processing. This is considered the first step and called input.
  2. Processing – Once the input is provided the raw data is processed by a suitable or selected processing method. This is the most important step as it provides the processed data in the form of output which will be used further.
  3. Output – This is the outcome and the raw data provided in the first stage is now “processed” and the data is useful and provides information and no longer called data. Output is also understood as meaningful information or useful information.

Stages of the Data Processing Cycle

As discussed earlier data processing have three broad stages which have sub stages or steps involved. These are the steps/process required in between these three broad stages. These deal with the collection of data, choosing the processing methods, practicing data management best practices, information processing cycle, making use of processed data for the desired purpose. Data cycle diagram is presented below. The steps include:

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Data Processing Cycle

  1. Data Collection: Collection process is the first step which provides the data. Collecting data is a hard work in its own, but is the most essential on which the results depend. This data collection can be done in various ways by primary or secondary sources. This data might include census data, data acquired by GDP or other monetary figures, data about a number of industries, profit of a company, etc. Depending upon the data requirement its source must be identified from which data will be collected. Also identification of datasets and data items is done at this stage.
  2. Preparation/ Sieving: Some people consider this as a part of processing but does not involve any processing. Preparation includes sorting and filtering of data which will finally be used as input. This stage required you to remove the extra or unusable data to make processing faster and better. This is a broad step in reducing the quantity of data to yield in a better result. It is also sometime referred as data cleaning.
  3. Input: This is the feeding of  collected data, raw and sieved data for processing. If the inputs is not given properly or entered wrong, then the result will be adversely affected. This is because software follows the rule of “Garbage in – garbage out.” Utmost care should be taken to provide the right data and minimum errors in data entry. The quality of input will determine the quality of output. Use verified data is available so as to improve the processed information.
  4. Processing: This is the step where data is processed by electronic data processing, mechanical processing, processing system or other means. The processed data is one who gives information to the user and can be put to use. The raw data cannot be understood and thus needs processing which is done in this step. Processing of data may take time depending processing power, complexity of the data, computer systems and the volume of input data. The step of preparation mentioned above helps in making this process faster.
  5. Output/ Result – This is the last step of the data processing cycle as the processed data is delivered in the form of information/ results in this step. Once the result or output is received, it may further be processed or interpreted. This is done by the user or software for further value addition. This output can also be used directly in presentations or the records. This output may even be saved as to be used as an input for further data processing which then becomes a part of a cycle which is being discussed. If this data is not used as input, then this complete process cannot be considered as cycle and will remain to be a one-time activity of data processing. For using this data as input, it must be stored or simultaneously be available for further processing. Data storage can be done by various means.

Distribution Process

All these steps or stages have a particular sequence which must be followed. If processing is done manually as the automatic processing have inbuilt algorithms with predefined steps. In automatic processing, the chances of error are drastically reduced. This happens only when the input is a correct data or data set.

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Most of the programs which process data completely or partially have a back-end with a pre-defined algorithm and sets of operation. A single software is performing all the required steps is considered to have a complete data processing cycle in its back-end. A combination of a different set of hardware and software is needed to complete the cycle in partial data processing. It becomes the responsibility of the person operating this set to feed and receive the output in a particular sequence.

Limitations of the Data Processing Cycle (what not to expect)

Data cycle in most of the cases is a complete cycle in itself. But as mentioned above a set of hardware and software might also be employed in some cases with special needs. In such cases, some things need to be taken care of to get the sensible and useful output. This depends on the correct sequence, operating skills, understanding of the steps forming the cycle. Partial output from one part which will be used as an input for next part. If a person/operator/machine or software fails to perform the steps in sequence then the output will not be useful.

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