Big Data in a Nutshell

Big Data in a Nutshell

In times of digitalization and Industry 4.0, the topic of Big Data plays an increasingly important role. Whether in industrial companies, social media or during personal shopping in the supermarket, huge amounts of data are generated and stored every day. NETZSCH Analyzing & Testing keeps up with the times and takes on these new topics in the field of thermal analysis. In the new blog series, our data scientists familiarize you with the new terms.

By Michaela Lang & Jigyasa Sakhuja, Data Scientists at NETZSCH Analyzing & Testing

Introduction

In times of digitalization and Industry 4.0, the topic of Big Data plays an increasingly important role. Whether in industrial companies, social media or during personal shopping in the supermarket, huge amounts of data are generated and stored every day. Such large data volumes, which can occur structured or unstructured, are called Big Data. The goal is to derive information from the collected data volume in order to gain insights depending on the needs of the application. Big data sets are usually so complex and large that they can no longer be processed using conventional methods, such as database systems.  For this reason, mathematical methods and procedures are used to analyze these data sets.

NETZSCH Analyzing & Testing keeps up with the times and takes on these new topics in the field of thermal analysis. In this blog series on the overriding topic of Big Data, we would like to inform you about the new terms such as Data Science and Machine Learning and explain their use in more detail.

Series 1: The impact of Big Data

Definition of Big Data

Big Data is the data that is increasing rapidly nowadays and enables methods that help the companies process the flood of information in a powerful and advantageous manner. On the one hand, it describes a very large amount of complex and fast-moving data and the term includes the digital technologies that are used to analyze this big amount of data on the other.

Benefits of using Big Data

In particular, talking about unstructured data, many companies create a lot of data but they do not know how to make it useful for their businesses. In companies, technical and economic data is often available in an unstructured form and very large quantities. In order to search through and access these data volumes quickly and efficiently, conventional approaches such as database systems pose a great challenge or are even no longer possible. That is why various techniques are developed for handling and processing a large amount of data. There are different processes from data storage to the analysis of the data. It is important to find the right approach for the needs and process structure of the respective company. The usage of Big Data has given a very good impact on the corporate landscape as the huge amount of available data is providing the companies to gain a completely new insight into their products, e. g., buying behavior, material properties or even the market risk.

Whether small or large companies, everyone can benefit from the use of Big Data methods if you know how to use it. The main advantage of all newly developed techniques is the possibility to link technical data with the business data of a company and to make correlations between the areas visible. This opens up completely new opportunities and can create new business models.

Big Data in thermal analysis and polymer-based composites industries

Companies which are dealing in the field of polymers receive additional benefits, as new polymers are being discovered with the help of machine learning (Montalbano, 2019). But also the material behavior of a polymer can be predicted and classified by the use of Big Data. Regarding thermal analysis and especially polymer-based composites industries, predicting the behavior of a polymer’s material influenced by changing parameter can optimize the process and make the industry very robust which leads to high efficiency and reduction of production cost.

How to use Big Data?

For the efficient handling of Big Data, a clearly defined structure for data storage as well as good data processing must be implemented. To make the data powerful, today’s keyword which is used is Data Science. In order to draw useful information from the collected data, it must be analyzed. As a prerequisite for this, the data must be carefully prepared. But just as important as the preparation of the data is the data quality itself. Not only is the quantity of data highly relevant, but also the information within the given data itself plays a big role in analyzing. This leads us to conclude: You can collect a huge amount of data, but without any data quality, you cannot use it reasonably and efficiently. The more information you can get within the data, the more quality you can gain. With the use of complex data analysis, the companies acquire new insights from this valuable data information and get the advantage of creating better decision making on their activities performed in the business.

Preview

In the next blog article, we want to show an overview of the possibilities and methods which are available to evaluate this large amount of data from various data sources. We would like to give you an overview what is known as Data Science and show what can be achieved with its application.

So stay curious about our next blog article of the Big Data series!

 

Citation Link : https://www.designnews.com/materials-assembly/researchers-use-ai-discover-new-polymers/67744341261255

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