Introduction


We live in an era that's data-oriented. Yes, the internet we use today for searching for information, doing online financial transactions, booking rides, etc., generates data. The amount of data is increasing every single minute. These datasets are raw and unstructured. One can utilize a huge amount of data to generate insights. This is possible only via data processing.
In this blog, we will be highlighting what data processing is. We will also discuss data processing methods in a detailed manner. Let's begin, stay tuned.

What is Data Processing?


The reconstruction of data into a usable and structured form is defined as data processing. The entire procedure of converting data is executed manually via a built-in sequence of operations. The majority of raw datasets are processed using computers. Hence, the data processing is usually automatic.
Once the data is processed, the output is obtained in any of the various formats - image, file, graph, table, audio, charts, etc. You can opt for the desired form of processed data depending on the type of software for data processing used.
Data processing is the modulation of all the data entered into the software. The main aim of data processing is to extract the most useful information out of huge datasets. And the information filtered out is crucial for any organization/firm/business. Because it helps them take the most relevant decision in the company's favor.

Why is Data Processing Needed?


Examples of Manual Data Processing include manual report writing, manual report calculation, manual processing, financial calculation, etc. These types of manual data processing take a lot of time and require you to engage many people. Hence, today, strong and coherent software tools have required help in processing all that data.
Below, we have cited a few reasons why data processing is needed.

1.  Time is precious & working manually on raw data is difficult. Data processing tools help businesses filter out relevant content.
2.  Data processing helps a business/firm arrange the filtered-out data insights into a homogenized form. These insights can easily be matched to big figures when required.
3.  Data processing makes one search for any relevant information at any point in time.
4.  Arranging raw data into well-structured charts requires time and money. Data processing makes this whole procedure more cost-effective. The required information gets filtered out in a hassle-free manner.
5.  The process makes data modification easy. One can edit the processed data within no time.
6.  Data processing is the key to data mining. It cuts off the extra cost of lengthy paperwork. The entire data can be processed and filtered out automatically.

What are the various Steps in Data Processing?


Data processing comprises 6 main steps. The steps are as follows:

1. Data Collection


The first step in the data processing cycle is to gather raw data. The pattern or classification of raw data highly impresses the output produced. Thus, raw data is usually collected from defined sources. Such sources are faultless and hence the data findings are valid and usable.

2. Data Preparation/Cleaning


The second step in the data processing cycle is cleaning the collected data. Data preparation can be defined as filtering the raw data to remove dispensable and inaccurate data. Raw data is examined to detect errors, duplication, miscalculations, or missing data. The prepared data is then remodeled into a suitable form for data analysis and processing.

3. Input


The third step in the data processing cycle is inputting raw data. Raw and modeled data is transformed into machine-readable form. It is then inputted into the processing unit. The data is fed in the form of data entry via an input device like a keyboard.

4. Data Processing


The fourth step is subjecting raw data to a variegated data processing method. Data processing depends on the source of data being processed. For example - online databases, connected devices, etc. for obtaining an output. ML (machine learning) and AI (artificial intelligence) algorithms are used to bring out a desirable output.

5. Output


The 5th step is all about obtaining an output. The processed data is finally communicated and displayed to the user in a readable form. The output is obtained in any of the formats - graphs, tables, video, documents.

6. Data Storage


The final step in the data processing cycle is storing the processed data. The output in the form of metadata is stored for further use. Data storage avails users of quick and error-free access whenever needed.

Types of Data Processing


There are 5 categories of data processing depending on two aspects 
A.  source of data
B.  processing unit's steps

1. Batch Processing: Batch Processing means collecting and processing data in batches. This type of processing is used for vast amounts of data.
2. Real-time Processing: Here, data is processed in a fraction of seconds. This type of processing is used for small amounts of data.
3. Online Processing: When the data is fed into the CPU in a computerized manner, it is called online processing. This type of processing is used for the continuous processing of data.
4. Multiprocessing: Data is distributed into frames and processed using two or more CPUs.
5. Time-sharing: This type of data processing is used for allocating computer resources and data in time slots.

Data Processing methods


Data can be processed by the following methods:

1. Manual Data Processing


As per the name, the data here is processed manually. Examples of manual data processing are calculating a report manually, verification of marks sheets, etc. All the steps in data processing - collection, modeling, calculation, and other logical operations are done with human intervention. No data processing software or tools are used here.

2. Mechanical Data Processing


When the data is processed mechanically via modern & up-to-date devices and machines, we call it mechanical data processing. The tools used for this type of processing are calculators, printing press, etc.

3. Electronic Data Processing


Modern technologies, software, programs, and tools are used for electronic data processing. This method is expensive and offers the quickest & most reliable processing results.

We hope this article has helped you in understanding about Data Processing, its methods and various types associated with it.