Statistics is part of our everyday life. Even if we do not directly work with statistical methods in our everyday work, we are faced with a multitude of statistics every day.
We learn about share prices, trends on the labor market, current election projections, or the evaluations of the English premier league via television, newspapers or the Internet.
In everyday use, the term “statistics” often refers to a data set – such as the medal distribution at the Olympic Games.
For statisticians, however, the scientific discipline is concerned with parameters that can be derived from statistical data, such as the mean value or median.
Big Data – The new oil of our time
In our society, data obtained by measurement or observation play an increasingly central and decisive role. It is not for nothing that they are described as the new oil of our time.
This applies both to data that is collected about us on a daily basis and to data, key figures, and measurements in a business context.
Due to new and rapid technological developments, the amount of data available from all business areas of a company is constantly growing. But what do you do with this data and what benefits can companies derive from it?
Companies and those responsible for data analysis are increasingly faced with the challenge of applying newly emerging analysis methods from “Big Data”.
They have to develop a new understanding of data analysis and identify and open up opportunities and perspectives.
Digitization in companies demands new skills
The ability to analyze and process large amounts of data in a “smart” way and thus create valid bases for entrepreneurial decisions becomes all the more important the more digitalization is practised in business organization.
This data analysis know-how becomes a key success and forms the basis for decision-making and strategy development in business.
In order to ensure that well-trained personnel is available, it is necessary to make learning in work-place the norm and to strengthen further training in working life.
In the future, initial training will be less and less adequate for the demands of professional careers, as knowledge becomes obsolete ever faster and rapid technological developments make new skills and competencies necessary.
From Big to Smart Data – Data Analytics in the focus of the new DGQ statistics courses
This view is particularly true of the requirements and the huge opportunities for companies in the field of data analysis.
The DGQ reacts to this and sets new accents in the tradition as a renowned training partner for statistics:
- Production data serve as a basis for optimizing machines and processes, forecasting the production balance, and ensuring product quality
- Process stability is controlled with data analysis as the basis for reproducible high quality
- Analytical capability is established to determine and predict the reliability of products
- Entrepreneurial decisions and corporate strategy benefit from insights from data
Opportunities from Big Data are used for faster decision making, more innovation, and competitive advantage
Statistical methods and models will continue to form the basis for obtaining valid findings.
Building on proven and still valid statistical methods, the DGQ shifts the focus of knowledge acquisition towards data analysis.
On the one hand, the updated offer includes proven fields of application of statistical methods, such as in the control and analysis of processes or the planning of experiments.
In addition, new methods and application possibilities of data analysis, such as the explorative analysis of large amounts of data, are included.
Participants will learn suitable statistical methods to use Big Data for their own purposes and to turn it into Smart Data.
The course focuses on the practical application of explorative methods. An explorative analysis of existing data makes it possible to recognize patterns in large amounts of data, to discover the causes of certain facts, and to draw the right conclusions.
New courses available from mid-2019
With the revision of its statistics courses, the DGQ is taking relevant steps in the direction of data analytics, so that quality and process managers will continue to prepare themselves comprehensively for the current challenges in the future.
From mid-2019, the new courses and certificates will be offered with different thematic focuses. Six courses combine the DGQ’s decades of experience in teaching practice-relevant