Data driven organizations more successful

Mon 18 November 2019

More and more companies analyse data. In 2018, 22% of all companies performed analysis on big data. Because of the increasing use of social media and mobile devices more data is being produced and registered. This amount of data offers possibilities: new insights arise with many chances to optimize processes and make decisions.

With the help of data you perform better. Data is the fuel for organizations to make better and faster decisions, to react to clients rapidly and to see opportunities or threats before competitors do. More than half of the companies that make databased decisions obviously experience the advantages.

Data engineering
More and more companies invest in data analysis. It is not easy to become a data driven organization. It requires broad and specialized statistical and corporate knowledge. A recent Gartner-report shows that almost half of the organizations has problems to bring data initiatives into production despite of huge investments. Here, data engineering plays an important role. By analysing, designing, realising and visualising data solutions, you make sure that data is used optimally to achieve the company goals.

Technical innovations
Established companies encounter more and more competition from technology-based newcomers. Specifically in the technical field the number of initiatives in this area increases rapidly. Applying automation and data driven projects is very important. With artificial intelligence and machine learning you develop predictive models and make sure that your company can keep up or even becomes a leader in the market.

Do you work with data analytics or are you starting in this field? Or do you want to make your company data driven? And do you wish to acquire basic or specialized knowledge of statistics and data analysis? In our courses you learn actual methods for retrieving important trends and structures from your data.

In 2020 you can attend the following courses:
Practical data science
Essentials of predictive analytics
Time series analysis and forecasting
Multivariate data analysis
Data mining & business analytics

Source: CBS, CM:


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