Our daily activities are increasingly shifting from the real to the digital world. Almost every action generates data records. Sensors and machines collect information from a wide variety of data sources, store it and process it accordingly. On the internet or through networked devices, each of us leaves digital footprints. New, huge amounts of data are created every second.
Data Science
Although hardly any companies underestimate the associated potentials and opportunities, many companies still find it difficult to profitably process and analyse the data and integrate it into smart business models or processes. With the methods of data science and artificial intelligence, usable patterns and structures in data are identified and, at best, immediately translated into automated actions. Data science and AI are thus the gateway to digitalisation. CRISP-DM, the well-known phase model, is used in many of our projects for structuring and is often combined with agile elements such as Scrum or Kanban. The Business and Data Understanding steps are just as important a part of our Data Science consulting approach as Data Preparation (Feature Engineering) and Modelling, which are often regarded as Data Science proper. We are convinced that an optimised solution to a problem starts with a precise understanding of the problem. Artificial Intelligence is often outlined as a purely self-learning system that does not need a "trainer", determines its own optimisation criteria and eventually replaces natural intelligence.
Data Science
For us, artificial intelligence is much more associated with sophisticated algorithms, which we use specifically with our customers to utilise optimisation potential. For example, we can use deep learning methods to improve text evaluations for sentiment analyses or integrate automated image recognition into prediction models. Artificial intelligence can also be used via speech recognition or chatbots to reduce your call centre workload.