Data is created almost every second whether you use the internet to study a certain topic, conduct financial transactions online, purchase meals, or anything else. The usage of social networking, internet commerce, and video streaming services has all contributed to the explosion in data. According to Domo’s research, every human on the planet generates 1.7MB of data every second. And to properly utilize and get insights from such vast amounts of data, data processing comes into play. We will explore data processing and methods of data processing further in this article.

What Is Data Processing?

Data in its raw form is not helpful to any company. The term data processing covers a variety of operations that are performed on raw data to turn it into usable information. In a company, a team of data scientists and data engineers often do it step-by-step. Before being shown in a useful format, Raw data is collected, filtered, sorted, processed, analyzed, and stored before being displayed in a usable format. Data processing is essential for firms to improve their business strategy and obtain a competitive advantage. Employees throughout the company may comprehend and use the data by translating it into usable representations such as graphs, charts, and texts.

What Are The Methods of Data Processing?

Methods of data processing include

Manual Data Processing:

This data processing approach is done manually. The whole process of data gathering, filtering, sorting, calculating, and other logical activities are performed with human intervention, without any other electronic equipment or automated software. It is a low-cost process that requires little to no tools, but it creates high mistakes, high labor expenses, and a significant amount of time and tedium.

Mechanical Data Processing:

In this case, data is processed mechanically using gadgets and equipment. Simple devices like calculators, typewriters, etc. fall into this category. This approach is suitable for doing simple data processing procedures. It has fewer mistakes than manual data processing, but as data volumes have increased, this approach has become more sophisticated and demanding.

Electronic Data Processing:

Modern data processing software and tools are required to process data. A set of instructions is given to the program to process the input and produce results. This technology is the most costly, but it provides the quickest processing rates and the best output dependability and precision. You can read about modern data analytics tools such as AI Data Analytics In Business.

The Future of Data Processing 

The future of data processing can be summarized in one word: cloud computing. While the basic steps of data processing remain unchanged, cloud technology has offered amazing breakthroughs in data processing technologies. And this provides data analysts and scientists with the quickest, most sophisticated, cost-effective, and most efficient data processing methods available today. The cloud enables businesses to combine their platforms into a single system that is simple to use and adjust. Cloud technology enables the smooth integration of new upgrades and updates to existing systems while also providing enterprises with enormous scalability. Learn more about the Impact of cloud computing in the Retail industry.

Why Choose IntoneSwift?

Modern business methods and strategies rely greatly on the effective use of data. It has become a key feature of corporate decision-making, and data processing is a critical component of this process. Aside from delivering all of the features mentioned above, IntoneSwift is a top-of-the-line data processing solution that has been tried and tested by industry leaders and experts alike. Its features include: 

  • Generates knowledge graph for all data integrations done
  • 600+ Data, and Application and device connectors
  • A graphical no-code low-code platform.
  • Distributed In-memory operations that give 10X speed in data operations.
  • Attribute level lineage capturing at every data integration map
  • Data encryption at every stage
  • Centralized password and connection management
  • Real-time, streaming & batch processing of data
  • Supports unlimited heterogeneous data source combinations
  • Eye-catching monitoring module that gives real-time updates

Contact us to know more about how we can help you.

Image by Pete Linforth from Pixabay