What is Data Processing?

            It wouldn’t be wrong to say that in the absence of data processing, both institutions and organizations don’t have any access to the sheer amount of data that helps them in gaining not only insights into sales but a competitive edge as well. Data processing takes place when data from different sources is collected and then interpreted into information that can be used later on. Normally, it is performed by a team full of data scientists or an individual data scientist. Though, it is important to ensure that data processing has to be carried out for a positive aim.

        The processing of data begins with raw data and converting into a format that is more readable like documents and graphs, casting it in the context and form which is important to be translated by computers and used by a number of workers or people.

Six Stages of Processing Data

        Data Collection Stage: In the whole processing of data, the first step is data collection. Using available and reliable sources, data is collected including data warehouses and data lakes. The well-design of sources is quite important just to ensure that the quality of information is top notch.

        Data Preparation Stage: With the collection of data, the stage of data preparation begins. Pre-processing is just another term that is used to refer data preparation and in this stage, the cleaning of raw data takes place and organization for the upcoming stage of data processing. During this stage, the available raw data is checked diligently to remove every possible error. The objective of this specific step is to delete incorrect, incomplete, and redundant data for the creation of high-quality data.

        Data Input Stage: Moving on, the clean data is placed where it belongs (data warehouse or a CRM), and interpreted into its understandable language. It is the first stage in which data starts to shape in useful information.

        Processing Stage: In the processing stage, the previously inputted data is really processed for translation. And processing is carried out using algorithms of machine learning, although the process itself might alter according to the data that must be processed (connected devices, social networks, and data lakes etc.) and for what it has to be used (medical diagnosis, customer needs, and evaluation of advertising patterns).

        Interpretation Stage: It is the stage at which the usability of data increases in terms of non-data researchers and scientists. It is readable because of translation and mostly on the form of plain text, images, videos, documents, and graphs.

        Data Storage Stage: The last stage is all about storing. After all the data is interpreted, it is saved for later use. Even though some information might be used immediately, much of it will be utilized for serving purposes later on. Moreover, it is very important to save the information properly.

         Overall, it can be said that data processing is what allows both organizations and institutes to advance forward and prepare for unforeseen circumstances in the market.