How to professionalize your data work and build competitive advantages with clear roles, smart organization and defined KPIs.

The core task of a data team is to extract, process, check and provide data from source systems in such a way that a so-called activation is possible at the end. This typically includes data connection, quality assurance, reporting, visualization and, depending on the level of maturity, forecasting or AI-based use cases. A data team is successful when other areas can actually act on the basis of their work.

A strong data team combines technical, analytical and business-related roles. The data engineer for the availability and accuracy of the data, the data analyst for reporting and visualization, and a data value creator who translates business requirements and ensures that data work contributes to business goals are central. Depending on the level of maturity and focus, a data scientist can also be useful if descriptive analysis is to become more prescribing data work with forecasts and recommendations.

It depends on the level of maturity, resources, and complexity of data work. A decentralized organization has often grown historically, but easily leads to silos and untapped potential. A central data team enables rapid initial success and clear control, but as the number of use cases grows, it is more likely to reach communication limits. A hybrid, federated model combines central standards with more subject-oriented analysts and is therefore often particularly effective when it comes to scaling data work while remaining close to business.

A data team creates added value when its work is not only technically clean, but is also used in the specialist areas and improves decisions. This requires joint KPI definitions, reliable data, realistic goals, rapid initial successes and continuous feedback structures. Technical quality can be ensured through proxy indicators such as automated tests or data checks, and functional benefits through the use, satisfaction and impact of reports in the specialist areas.