In today’s economic world, data are one of the most important resources that companies have. In the first chapters of this master thesis the essential concepts relating to data and data management are explained. In addition, the currently used data analysis methods are described, and the statistical instruments are shown on which these methods are based. In the second part of this thesis it has been evaluated if the Austrian industrial companies have made the necessary steps to ensure an effective and efficient handling of data. For this purpose, a survey has been sent to Austrian industrial companies. After the evaluation of 141 replies, the following trends can be outlined: •Only a few of the industrial companies in Austria have specifically defined positions for data management. •A majority of the companies have at least in a few departments an implemented data management. •In most industrial companies a standardization of the evaluation perspective and of KPI’s is done. •Big data projects, which allow more complex data analysis, are conducted by less than 50% of the respondents. It’s also stated by most companies that this topic is not considered as a key issue in the future. •The companies realize that they have to catch up on a few data related topics. •There is a clear correlation between the turnover of a company and the implementation of a company-wide data management. •Even if there is a defined data controller in the company, communication is stated as one of the main problems in the handling of data. •Very few industrial companies use modern data architectures or advanced data analysis. •Austrian industrial companies are aware that forward-looking data analysis will be predominant in the future. This master thesis provides a good overview of the current state of the data management of Austrian industrial companies and shows where they are well-positioned and where they need to catch up. The results of the conducted survey are also compared to other studies on this subject to point out territorial differences.