Whether the internet is used to research a topic, make transactions online, food ordering, data is continuously generating each second. The amount of data has increased due to the increased utilisation of online shopping, social media and streaming services. A study has estimated that 1.7MB of data is generated each second for every single human being on this earth in 2020. To avail and get intuitions from such huge amounts of data – data processing is useful.
So what is Data Processing? To be put in simple words is the collection, manipulation, and processing of collected data for the intended use. It translates huge amounts of collected data into a desirable form used by commoners to analyze and interpret the meaning of data processed. Data processing in computers refers to the manipulation of data by computers. This is inclusive of output formatting or transformation. Data flow through the memory and CPU to the output device and of course, the reformation of raw data into machine language.
Concept of Data processing is collecting and manipulating data into a usable and appropriate form. The automatic processing of data in a predetermined sequence of operations is the manipulation of data. The processing nowadays is automatically done by using computers, which is faster and gives accurate results.
Thereafter, the data collected is processed and then translated into a desirable form as per requirements, useful for performing tasks. The data is acquired from various sources like excel file, database, text file data, and unorganised data such as audio clips, images, GPRS and video clips. The most commonly used tools for data processing are Storm, Hadoop, HPCC, Statwing, Qubole and CouchDB. The output is worthwhile information various file formats like a chart, audio, table, graph, image, vector file depending on software or application necessary.
Therefore the meaning of Data processing is a method of collecting raw data and converting it into useful information. Data Processing is performed in a predetermined procedure by a team of data scientists and data engineers in an organization.
Data processing requires six steps, and those are:
The different types of output files in data processing are –
The three prominent data processing methods are as follows:
The types of data processing are as below:
E.g., withdrawing money from ATM
E.g., barcode scanning
E.g., weather forecasting
In the modern era, most of the work relies on data, therefore collection of large amounts of data for different purposes like academic, scientific research, institutional use, personal and private use, for commercial purposes and lots more. The processing of this data collected is essential so that the data goes through all the above-stated steps and gets sorted, stored, filtered, presented in the required format and analyzed.
The amount of time consumed and the intricacy of processing will depend on the required results. In situations where large amounts of data are acquired, the necessity of processing to obtain authentic results with the help of data processing in data mining and data processing in data research gets inevitable.
Finally, to define data processing in simple terms, it is the procurement of worthwhile information by conversion of data. The processing of data is done in six stages which are data collection, sorting of data, storage of data, processing of data, data presentation and data analysis.
The three prominent methods of processing data are Mechanical, Electronic and Manual. Data processing is crucial for organizations to create better business strategies and increase their competitive edge. By changing the data into a legible format like graphs, charts and documents, workers throughout the organization will be able to perceive and use the data to analyse and interpret according to their requirements.
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