Data engineering and analytics lead to long-term success in data-driven solutions, be it classical data analytics, Big Data, or Artificial Intelligence.
Autonomous driving, Industry 4.0, Internet of Things, and Big Data represent innovations that are empowered by software. The digital transformation leads to new challenges that must be mastered with regard to the development of data-driven solutions. Not only the technical processes, resp. the business processes, that are controlled in this manner are becoming more complex: Systems are also increasingly interconnected in networks in order to offer customers added value compared to stand-alone solutions. The digital transformation and system integration also result in the creation of completely new business models – for example based on Big Data Analytics for so-called data-driven business models.
Data engineers and data analysts know how an organization needs to be set up in order to be able to address these challenges through systematic elicitation and smart analysis of data and information while creating value for its customers.
We pursue an empirical approach where we:
- Identify improvement goals
- Collect data about the corresponding processes
- Identify weak points
- Initiate improvement measures and subsequently analyze their effects