Technical articles, white papers and more

Your success with data analytics and artificial intelligence

Benefit from current practical examples, white papers, free magazines and much more. In our service portal, you will find information, trends, tips and tricks relating to data analytics and artificial intelligence. Our experts will support you with comments, experiences and best practice examples. Discover our service portal now for new impulses in everyday life with data analytics and artificial intelligence.

Offers and services

For your success with data analytics and artificial intelligence

Whitepaper: 6 steps to AI maturity

The 6 phases that companies and employees go through when introducing and establishing AI.

Comprehensive guide and maturity model to determine your own position on the AI learning journey and successfully implement AI initiatives.

Factsheet: "The ABCs of Data Science - Your entry into the world of data science"

What does machine learning actually mean? What can data science do in a corporate context? What data science tools are available? And do I already have to be a data expert to attend a data science training course and apply data science in my department?

"The ABC of Data Science" gives you an introduction to the world of data analysis and shows you how you too can use data science profitably in your company.

Practical example: "Data science in controlling"

Pay on time or take advantage of discounts? How to use data science to intelligently design your payment processes!

The management of a company wanted to find out the best time to settle outstanding liabilities. In this practical example, you can read about the approach taken and the analysis methods used to ultimately achieve significant improvements in accounting.

Practical example: "Data science in marketing"

How to increase the conversion rate in your online store with data science

A manufacturer of electrical appliances launched a new online store that had a low conversion rate despite high visitor numbers. Read this practical example to find out which approach was chosen and which analysis methods were used to increase the conversion rate and thus boost sales via the new sales channel.

Practical example: "Data science in sales"

How to achieve successful business deals with automated lead prioritization

A software company generated a large number of new leads through marketing and sales activities. Read this practical example to find out which approach was chosen and which analysis methods were used to prioritize leads based on data so that promising leads could be processed first. 

Practical example: "Data science in banking"

How you can sustainably increase the profitability of your credit card business with data science

A bank's credit card business was not generating the hoped-for profits, which is why the pricing strategy needed to be optimized. Read this practical example to find out which approach was chosen and which analysis methods were used to prevent customers from dropping out due to increased interest costs. 

Hot Skill: Python

7 reasons why it's worth learning Python now! 

Read more, 

  • how versatile Python is.
  • why Python is THE tech skill of the future.
  • and why it's worth learning Python right now!
Practical example: "Data science in production"

How to minimize production machine downtimes with data science

A mechanical engineering company was planning a new service offering, the core of which was to be the early prediction of possible machine failures. In this practical example, you can read about the approach chosen and the analysis methods used to predict machine failures and thus achieve a 20% reduction in maintenance lead times.

We are happy to help

Get in touch with us

We are there for you Monday to Friday from 8:00 to 17:00.

Stephanie Göpfert

Head of Customer Service

Mandatory fields
In order to be able to process your request, the processing of the data you have provided is necessary. By submitting the contact form, you agree to the processing of your data (see Privacy Policy, section IV). Your data will be deleted after the purpose ceases to exist. You can object (see Art 21 GDPR) to the processing of your data at any time.