In this current generation of information, data generation takes place every second. With advanced technology, there is increasing use of mobile by people around the globe. Before we jump onto how Data Processing nourishes business globally, we must understand the term Data Processing.
Table of Contents
Data Processing – What is it actually?
Just like crude oil, data in its crude form is useless to any company. Crude oil is processed to extract various products, from petroleum and diesel to LPG. Similarly, data is collected and processed to give it a sculpted shape to use it.
Collection > Preparation > Filtering > Sorting > Processing > Storing
Data processing is essential for businesses to ideate new plans and innovative strategies. This helps them strengthen their corporate strategy. The data analysts can show the processed data in pie charts, bar graphs, line graphs, tables or any other interactive form. This helps anyone glancing at the processed data to analyze it quickly. Therefore assisting companies to grow more!
Now that we know what data processing is, we shall see the Types, Methods, and Steps of Data Processing.
Types of Data Processing:
- Batch Processing
Batch processing is used for massive data sets. This batch processing helps the organizations in handling the payroll system.
- Real-Time processing
Data is processed for small data sets within a fraction of seconds when the input is provided—for example, withdrawing cash from an ATM. The records are added and processed in real time. Therefore, providing a detailed analysis of the spending by a customer.
- Online processing
Online processing processes the data continuously, such as reading bar codes. The cloud server stacks the data and tracks the record of a particular product using the barcode, thus enabling the businesses to understand which product is selling more and which is less.
- Multiprocessing
Data is divided into frames within a single computer system and processed using multiple CPUs. Meteorological scientists can use this type of data processing to forecast the weather.
Methods of Data Processing & their advantages/disadvantages
- Manual Data processing
It is a method that requires little to no equipment.
- High labour costs
- High error rates, and
- Long processing time.
- Mechanical Data processing
Machines are used to process data mechanically.
- Fewer human errors
- Simple Operations
- With more data, it becomes uneconomical
- Calculators and simple machines are used
- Electronic / Automated data processing
- Uses highly advanced software
- Minimal human intervention
- Lesser Errors
- Most expensive but economical in the long-run
- Highest accuracy
- Quickest processing time
With this automated data processing, the data’s reliability increases, giving rise to the best working strategies. The processing speed helps the analysts come up with working plans to deliver the best methods to help businesses grow and reach great heights.
Steps involved in Data Processing:
- Data collection
Before processing, the data scientists must acquire the data first. The data should be relevant to the needs of the business. The data collection sources and the methods should be reliable, as this is crucial. If this step is wrong, the entire following steps would be of waste. Therefore, utmost care should be given while collecting data.
- Data preparation
Data preparation is necessary after data collection for better results. This step decreases the time required to process the data significantly and the risk of errors that might crop up at a later stage. In this step, the data scientists should eliminate incomplete and irrelevant data. Therefore, keeping ready the high-quality data for processing. The entire data set must be reviewed twice for errors as it is submitted for the next stage.
- Input
At this point, any missing or incorrect data can make the results invalid. Therefore, correct data in an understandable form is fed to the software.
- Processing
The data is processed per the required output and the specified input using machine learning algorithms. The data processing in the desired format is the end product.
- Data Interpretation / Output
After further interpretation, the information can be presented in a way that is appropriate for end users. The data output is understandable by a layman. By doing this, processed data is made more uncomplicated so that organizations may utilize it to analyze and develop strategies to grow businesses.
- Storage
Security of the processed data is crucial. As and when needed, saved data should be easily accessible only to authorized personnel.
The processing element is cyclical, meaning that each stage is required but that the output and stage phases may result in a repetition of the data collecting step, beginning a new cycle of data processing.
Conclusion
Data processing may be quite helpful in organizing everything and ensuring a seamless workflow that pleases the users and managers of the data. With properly analyzed data, any organization can grow exponentially if it properly taps the potential of the collected data.
With ever-increasing data, the analysis and processing of the data become very hectic. Therefore, choosing the best methods to process the data will make the business stand ahead of the competitors on the growth ladder. Nourish your business growth by processing the data collected – first-party, second-party or third-party, does not matter. Collect reliable data and tap the benefits today!
