Everything you wanna know about Data processing

Either you own a big corporation or a small startup enterprise or you are just first-grade Computer science student, you must have heard of this term. Data processing is generally the conversion of data into desired and usable form.


Every organization system that somehow involves network resources needs to have a data processing unit. The processing or conversion of data is carried out by a sequence of operations. Most of the data processing is carried out by high-speed computers; however, they can also be carried out manually. This blog is intended to provide you every information you want to gather about “Data processing.” To comprehend completely about data processing first we have to outline some questions that we will figure out later in the blog.

  1. How many ways we can process our data?
  2. What are the predefined steps of data processing?
  3. The importance of data processing in the modern world?
  4. What are the various methods of data processing?
  5. Data processing as a career approach?

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Data processing ways

Usually, there are three types of data processing methods which people opt for their organization depending on the size of the enterprise. It implies that if you own a day to day business, you are more prone to use the manual data processing. Whereas if you own a big corporation, you are going to choose a big storage facility for data processing. The three types of data processing are mentioned below.

  • Manual processing is when the owner does not use any tool, machine or electronic device to store data. Data is processed manually using papers without the use of any calculation and logical unit.
  • Mechanical data is when the owner uses a simple electronic device such as typewriters and calculators. This method is very adapt for small time business owners and shopkeepers for secure data processing.
  • Electronic data is the most modern technologies to store data for a big enterprise which relies on the big storage facility. These facilities use the fastest, an accurate and highest reliable algorithm for data processing. A logical unit is equipped to process data by using a set of instructions and input methods to store the data. This blog is mainly focused on Electronic data processing rather than on the first two methods.

Date processing: an overview

Processing of data is undertaken by sort of activities which are helpful in the collection of data. The collected information needs to be sorted, stored, analyzed, processed and presented. There is a predefined process for data processing which can be distributed in 6 stages.

Data Collection

The process includes collecting the data in different forms so that it can later be processed. Once it is obtained the need for a data storage facility emerges. Data can be collected physically by the use of paper or notebooks which is now termed as an old school method. Physically collecting data leads to a dozen issues, just for the example, it is not an eco-friendly way to store data.

Also Stacking tons of paper and retrieving can be a challenging task. But this blog emphasis more on the automated types of data processing. With the revolution in data mining and the emergence of the big data warehouse, almost every enterprise relies on data processing.

Data analysis

The next step in the process of data processing is analysis. This implies that we have to select only the relevant data that can be used to create a piece of information. Other irrelevant data and sacks of illogical data need to get dumped. This will eventually lead to efficency in storing and retrieving data. Data analysis reduce the possibility of errors and prevent misleading data to affect our judgement.

Data Input and sorting

The process of storing and sorting the data and transforming into the computational language is known as data input. Programming languages such as MySQL is used to store data into cloud storage. For this process, a data professional or analyst is hired so that while inputting data no useful piece of information gets left behind.

Data Processing

The next step in the process is to manipulate the data using an algorithm to produce meaningful and useful information using some high-end software. The machine algorithem translate the input data and process it for user’s interpretation.

Data Output

Now when we have successfully stored, analyzed and processed the data, it can be made available for the users. The user can read the meaningful data in formats such as reports, video, audio, text or graphs. The overview of processed data will eventually help the user in the decision-making process. Members of organisation can now begin to analyze the data patterns for building their future business prospects.

Data Storage

The last stage in data processing is storing the stacks of useful data in a big storage facility. Sorted data can be retrieved anytime in future for the user when required. A properly stored data in a business enterprise is essentially important for compliance with the data laws such as GDPR.

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Importance of data processing

In every sector, whether it is academic, private, scientific research, commercial use, data processing is a fundamental aspect. The overview of collected and processed data could impact decision making. Data processing eventually affected future business operations.

Nowadays the need for large storage warehouse is inevitable for multinational companies that rely on data storage. In the modern world, the use of cloud computing and significant changes in data mining have affected the old norms of storing data manually.

No doubt data processing isn’t a novel aspect, but software products and near-constant technologies are capable of leaving anyone’s head spinning. Sorting and fast processing of data are highly recommended to make a business sustainable. Each stage beginning from the collecting to presenting the data output for presentation is crucial in creating any business successful.

Today’s competitive and agile environment depends on having an active, accurate and transparent data processing strategy. While the process has remained the same still the emergence of cloud computing has shifted the interest of big enterprise. The cloud computing delivers the fastes, cost-effective and most advanced methods of data processing.

Future of Data Processing

The future of data processing is in the last stage of its process which is data storage. Data needs to be easily accessible, and thus many of the big corporations are moving towards the cloud storage. Cloud storage is the most prominent feature of future Information sector that depends on the server storage warehouses.

Enterprise can easily buy such places at a fixed cost and store their business transaction data. The efficiency and accurate retrieving of data from cloud computing put it one spot ahead of its competitions. It is designed mainly focused on the big data, the data which is too heavy for old traditional data processing units.

Smaller enterprises could also benefit from cloud computing as it gives them a platform to grow. Many cloud storage facilities provide flexible and convenient storage at a discounted rate, thus making the old norms of data storage obsolete.

Data mining is also a crucial aspect in database management and future of data processing. The data mining is the study of interesting, useful patterns and relationships in a significant volume of storage. The field combines tools from artificial intelligence and stastics to analyze an extensive collection of data. Data mining could be very helpful in sectors such as government security, medicine research, and banking.


Learning the advanced data processing techniques and language could be a viable prospect in any IT career. 
SQL is wildly used as a Database management language in every project as a back end language. Almost every business needs to have a fast data management system to survive. If they fail to retrieve back data faster, it can eventually lead to a vast impact on their economy. Each task in data processing is equally essential, and carelessness in any one of them could lead to mass blunder, I hope I have covered all the question we needed to figure out in the blog.

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