EnBW Energie Baden-Württemberg AG intends to procure a multi-persona Self-Service Data and Analytics Platform to enhance data accessibility, improve cross-functional collaboration, and strengthen analytical capabilities across the Trading business function. EnBW intends to procure a self‑service data and analytics Software as a Service (SaaS) platform to support analytical, modelling and data‑driven activities across its trading teams and associated business functions. The objective is to obtain a secure, scalable and enterprise‑grade solution capable of operating within a complex, regulated and data‑intensive trading environment. The SaaS platform will be used by trade, portfolio management, risk management, quantitative analytics, data science and supporting business functions. The tool is expected to support structured data processing, development and operation of analytical workflows, and collaborative usage across business units. It should enable both code-based and low-code/no-code usage patterns, allowing technical users (e.g. data scientists and quantitative analysts) to develop advanced analytics while also enabling non-technical users to configure, execute and monitor workflows within governed environments.

Self Service Data and Analytics Tool as a SaaS Solution

"EnBW intends to procure a self‑service data and analytics Software as a Service (SaaS) platform to support analytical, modelling and data‑driven activities across its trading teams and associated business functions. The objective is to obtain a secure, scalable and enterprise‑grade solution capable of operating within a complex, regulated and data‑intensive trading environment. The SaaS platform will be used by trade, portfolio management, risk management, quantitative analytics, data science and supporting business functions. The tool is expected to support structured data processing, development and operation of analytical workflows, and collaborative usage across business units. It should enable both code-based and low-code/no-code usage patterns, allowing technical users (e.g. data scientists and quantitative analysts) to develop advanced analytics while also enabling non-technical users to configure, execute and monitor workflows within governed environments.