Data Science, AI, ML, AI - A definition of the most important buzzwords

What's data science?

The term "data science" is often referred to as data science in the German-speaking world. In terms of content, this refers to the extraction of knowledge from data, for which the WDL uses various scientifically based methods and algorithms. The aim is to identify new findings and patterns for the user by evaluating large company data and thus, for example, to create added value for further planning. Data Science comprises many methods which have in common that they can be applied in particular to extremely large data sets. For example, the WDL deals with the following methods:

  • Data Mining
  • KI/AI
  • Neuronal networks
  • Machine Learning
  • Data Analytics
  • Big Data
  • Decision and regression trees
  • Statistical models
  • Artificial neural networks
  • Meta algorithms such as XGBoost or Random Forest
The WDL currently has more than 40 experienced data experts specializing in various areas of data science. In the context of data science, these not only evaluate your existing internal data from the past, but also enrich it with additional external data in order to gain insights for the future.

What is artificial intelligence?

Artificial Intelligence (AI) is a branch of computer science that deals with the automation of intelligent behavior and machine learning. By programming a computer, certain human decision structures are simulated so that the machine can solve tasks relatively independently. Such tasks otherwise require intelligence when processed by humans. AI methods are used in particular where the cognitive capacity of humans is insufficient and the amount of data is extremely large. Small and medium-sized companies in particular often ask themselves whether the use of AI methods is also suitable for their own company and whether there is sufficient suitable data available in their company. The WDL can support you in this decision: Anyone who already knows today what is likely to happen tomorrow will be better placed to hold their own in the market. We know from experience that even smaller companies have sufficient data for the efficient application of AI. Often, however, it is not the missing data that is problematic in an analysis, but a bad data model or a missing objective. The correct preparation and meaningful combination of different data sources is relevant in order to be able to use data as a basis for future corporate decisions. A target-oriented data preparation and strategy are important for chances of success and competitive advantages. The WDL with more than 25 years of experience in Advanced Analytics. We can guarantee you a safe and meaningful application of AI methods, so that you as a small or medium-sized company can also be a big step ahead of your competitors in the future.

What is Machine Learning (ML)?

Machine learning is an area of artificial intelligence (AI) in which knowledge is generated from experience. The artificial system learns patterns and laws from given example data sets and can generalise what it has learned after the learning phase has ended. IT systems can dynamically recognize patterns in the given data and then assess unknown data and transfer the learned knowledge to new data in order to develop solutions or improve results and predictions based on learning processes. The technology behind machine learning is neural networks. The WDL uses machine learning, for example, to detect cases of fraud, analyze stock markets or determine future customer buying behavior. If you are interested in such questions, a data science project with the WDL would be a possibility to generate such information. We help you to find out what will happen in your company in the short and long term.

What's the difference between Machine Learning (ML) and artificial intelligence (AI)?

Machine learning and artificial intelligence are two keywords that are often not used in a differentiated enough way in the big data context. Artificial intelligence is understood as a broader concept in which machines are able to perform tasks in an "intelligent" way. Machine Learning is understood as a current application of the AI, in which the machines are given access to data and can then learn for themselves.

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