What is Data Processing?

Introduction to Data Processing

Data processing is the collecting and manipulation of data into the usable and desired form. The manipulation is nothing but processing, which is carried either manually or automatically in a predefined sequence of operations. In past, it is done by manually which is time-consuming and may have the possibility of errors during in processing, so now most of the processing is done automatically by using computers, which do the fast processing and gives you the correct result.

The next point is converting to the desired form, the collected data is processed and converted to the desired form according to the application requirements, that means converting the data into useful information which could use in the application to perform some task. The Input of the processing is the collection of data from different sources like text file data, excel file data, database, even unstructured data like images, audio clips, video clips, GPRS data, and so on. The commonly available data processing tools are Hadoop, Storm, HPCC, Qubole, Statwing, CouchDB and so all

And the output of the data processing is meaningful information that could be in different forms like a table, image, charts, graph, vector file, audio and so all format obtained depending on the application or software required.

How Data is Processed?

Data processing starts with collecting data. The data collected to convert the desired form must be processed by processing data in a step-by-step manner such as the data collected must be stored, sorted, processed, analyzed, and presented.

So this broadly divided into 6 basic steps as following discussion given below.

• Data Collection
• Storage of Data
• Sorting of Data
• Processing of Data
• Data Analysis
• Data Presentation and conclusions

Let’s discuss in details one by one:

1. Data Collection

As already we have discussed the sources of data collection, the logically related data is collected from the different sources, different format, different types like from XML, CSV file, social media, images that is what structured or unstructured data and so all.

2. Storage of Data

The collected data now need to be stored in physical forms like papers, notebooks, and all or in any other physical form. Now because of the data mining and big data, the collection of data is very huge even in structured or unstructured form. The data is to be stored in digital form to perform the meaningful analysis and presentation according to the application requirements.

3. Sorting of Data

After the storage step, the immediate step will be sorting and filtering. The sorting and filleting are required to arrange the data in some meaningful order and filter out only the required information which helps in easy to understand visualize and analyze.

4. Processing of Data

A series of processing or continuous use and processing performed on to verify, transform, organize, integrate, and extract data in a useful output form for farther use.

5. Data Analysis

Data analysis is the process of systematically applying or evaluating data using analytical and logical reasoning to illustrate each component of the data provided and to get the concluded result or decision.

6. Data Presentation and Conclusions

Once we come to the analysis result it can be represented into the different form like the chart, text file, excel file, graph and so all.

Single software or a combination of software can use to perform storing, sorting, filtering and processing of data whichever feasible and required. It may be carried out by specific software as per the predefined set of operations according to the application requirements.

Different Types of Output

The different types of output files as –

• Plain text file – These are exported as notepad or WordPad files. These are the simplest form of the data file.
• Table/ Spreadsheet – In this file format, the data represent in rows and columns, which help in easy understanding and analysis of data. This file format to perform various operations like filtering & sorting in ascending/descending order and statistical operations as well.
• Graphs and Charts – The graphs and charts format is standard features in most of the software. This format is very easy to analyze the data, not required to read each numeric data which takes a time consuming only in one look can understand and analyze the data.
• An Image File or Maps/Vector – If the application required to store and analyze with spatial data the option to export the data into image file and maps file or vector files is of great use.

Along with these, the other format can be software specific file formats which can be used and processed by specialized software.

Different Methods

There are mainly three methods used to process the data, these are Manual, Mechanical, and Electronic.

1. Manual: In this method data is processed manually. The entire processing task like calculation, sorting and filtering, and logical operations are performed manually without using any tool or electronic devices or automation software.

2. Mechanical – In this method data is not processed manually but done with the help of very simple electronic devices and a mechanical device for example calculator and typewriters.

3. Electronic – This is the fastest method of data processing and also modern technology with the modern required features like highest reliability and accuracy. This method is achieved by the set of programs or software which run on computers.

Types

On the basis of steps they performed or process they performed. It likes:

• Batch Processing (In batches)
• Real-time processing (In a small time period or real-time mode)
• Online Processing (Automated way enter)
• Multiprocessing (multiple data sets parallel)
• Time-sharing (multiple data sets with time-sharing)

Why We Should Use Data Processing?

Now a day’s data is more important most of the work are based on data itself, so more and more data is collected for different purpose like scientific research, academic, private & personal use, commercial use, institutional use and so all. It is necessary to process this collected data so that all the above – mentioned steps are used for the processing which is stored, sorted, filtered, analyzed, and presented in the required usage format. The time consuming and complexity of processing depending on the results which are required. In the case of huge data collection or the big data they need for processing to get the optimal results with the help of data mining and data management it becomes more and more critical.

Conclusion

It is the conversion of the data to useful information. The data processing is broadly divided into 6 basic steps as Data collection, storage of data, Sorting of data, Processing of data, Data analysis, Data presentation, and conclusions. There are mainly three methods used to process that are Manual, Mechanical, and Electronic.

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