Data Projekte
Data Projekte

Guest Lecture: Data Projects in Practice

On 22.05.23, the students of the THM Business School in Giessen were able to experience “a day in the life of a data guy” – namely that of our Amir Rahbaran, Unit Manager in the field of Data Analytics. In his guest lecture, the master’s students of digital business and corporate management had a lot to learn about the daily challenges of data projects as well as the ideal solution path.

The exciting topics included questions such as: How do you get from the customer’s request “We want Artificial Intelligence” to the final solution, which work steps are behind it, which data experts are involved in data projects?

Data projects in practice - seeing the big picture

In practice, data projects target specific business goals and purposes. These usually include improving business processes, optimizing products or services, identifying patterns, predicting trends.

Before implementing a digital solution, one often comes to the realization that the current data is not (yet) suitable for the projects. The current data quality often suffers due to incompleteness, duplications, various formatting or even partially irrelevant data. These problems must be solved before the core of the project can be addressed.

As an end-to-end service provider, we offer our customers IT solutions with the greatest possible added value. Therefore, we identify what the business goals and situation are. For this, stakeholder management is our top priority! We take an iterative approach with needs-based communication. Our motto here is “think big. start small. move fast”. Through feedback loops with our customers, we optimize the data projects and develop them further quickly.

One point that is part of optimization is scalability. Applications should always be designed so that as data volumes and requirements grow, solutions grow with them and get better. In order to process large amounts of data efficiently, suitable data infrastructures, tools and technologies must be used in the implementation.

Responsibilities and roles in data projects

Just as instrumentation and debugging are the first steps in data projects, various data experts are also involved in the respective project phases. This is because data projects usually require the cooperation of different areas: Data Scientists, Data Engineers, Data Analysts and experts from other areas work together to successfully implement the project.

For example, a data engineer makes the company’s data accessible and available. An analytics engineer, in turn, arranges the data so that it can be easily analyzed, visualized, and reused by the data analyst. Finally, the Data Scientist deals with advanced statistical methods and machine learning. Want to learn more?

Both the work steps, but also our customer projects in the data area are very multifaceted. For example, for an FMCG company (S&P 400), we merged sustainability-related data with specific CO2 benchmarks through data-driven insights into its global supply chain. The data can be used to improve CO2 emissions. Read more

Data and business experts for successful projects

Amir’s key take-aways at the end of the guest lecture: Data projects are best implemented with data quality, stakeholder management and an iterative approach! We would like to thank the THM Business School for allowing us to be with you and are pleased that we were able to give the prospective experts insights into the data field! Click here to read the THM Business School’s article about our guest lecture: A day in the Life of a “Data Guy”.

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