What is Big Data Analytics 2

Simply put: what is big data?

What are the advantages of using big data?

Classic relational database systems in particular have problems processing large amounts of data that are above average. Accordingly, the evaluation of such data falls within the scope of big data software. Here the providers rely on new types of data storage and analysis systems. As a rule, these access numerous processors and thus improve the speed of data processing. This has blatant advantages when processing many records as well as when processing numerous columns within a single record. The import and export of large amounts of data can also be carried out faster and more efficiently. After importing, all data can be called up in real time. In addition, corresponding software solutions are characterized by low latency and processing times - even for complex inquiries. Several queries can be executed in parallel without any major loss of performance. Ultimately, different types of information such as numbers, images or even texts can be examined for relevant information. Nevertheless, the development of the corresponding software is still in its infancy.

Examples of application areas for big data in companies

In fast-moving markets like today, competitive advantages are essential to building a good business position. This is where the data analysis comes into play. By analyzing large amounts of data, trends and patterns in the market can be identified and thus competitive advantages can be generated. However, the realization of potential savings and the creation of new business areas are sometimes based on the results of these data evaluations.

Example 1: credit scoring in banks

In particular, the granting of loans can be improved with the help of big data. In this way, the creditworthiness of a large number of customers can be evaluated within a very short time with the help of a corresponding data analysis. The results of such big data scoring far exceed the classic creditworthiness decisions in terms of their objectivity and efficiency.

Example 2: influencing purchasing behavior in direct marketing

Marketing is a classic area of ‚Äč‚Äčapplication for big data analyzes. In marketing, however, it is less about the data itself and more about the knowledge that can be drawn from big data. The right decisions can be made on this basis and the most profitable measures can be implemented. The evaluation of the data provides important and fundamental knowledge about the customers, who they are, what they want, where they shop and get information and how they want to be contacted.

With the results of the big data analysis, marketing experts learn how customer loyalty can be influenced and how lost customers can be won back. And this knowledge in turn enables a targeted, effective use of the marketing budget.

Example 3: Risk prophylaxis

Our last application example for big data in companies deals with fraud detection - known in German as risk prophylaxis. Again and again customers use fraudulent scams to steal a product or service. With the help of extensive data analyzes, possible irregularities can be identified at an early stage, which can then be checked more closely. Unwanted or incorrect transactions can also be identified in this way with a minimum of effort.

What are the challenges when choosing a big data software?

In the past few years in particular, the amount of data available has increased continuously, so this problem is not completely new for companies. Rather, the challenge for companies is to implement the often increasing, self-imposed requirements for data processing and evaluation.

Over the past few years, BI software has gained increasing strategic importance for companies. This in turn led to an increase not only in the number of users, but also in their expectations with regard to the topicality and short-term availability of the data. In addition, the relevance of the query performance of the respective systems also increased.

Overall, these high requirements only illustrate the challenges of the business world. Companies that react quickly, in particular, can use Big Data Analytics to gain competitive advantages in a highly competitive business environment.