The Customer:
Founded in 1898, Rheinisch-Westfälische Elektrizitätswerke (RWE) is one of the world's largest energy producers and a leading provider of renewable energies worldwide. There are two main subsidiaries: RWE Supply & Trading (RWEST) focuses on energy trading while RWE Offshore Wind specializes in offshore wind power-based sustainable electricity generation. The latter is the world's second-largest offshore wind power generation and Europe's third-largest company in renewable energy, with an international footprint in Europe, U.S., and select Asian markets.
RWEST's Essen headquarters support around 2,000 specialists from more than 70 different countries trading 24/7 (renewable) electricity, (green) gas, commodities, and CO2 emission allowances. RWEST also develops innovative energy supply solutions and risk management concepts for industrial companies, with a portfolio of customized products and services around renewable and conventional electricity, as well as upcoming gas and liquefied natural gas (LNG) markets.
The Challenge:
RWE needed a completely new data environment to meet current and future requirements of an increasingly global business. It required the implementation of a data strategy in alignment with the company's global initiative to enable trader and analysts faster access to trading data. To support these initiatives, RWE looked to establish a data culture based on shared information and ongoing knowledge transfer for intensifying/improving collaboration.
With RWE as a global player in the renewable energy market, RWEST bolstered its expansion efforts to include major cities like London, and New York, as well as key growth markets—particularly in Asia. Crucially, the firm's management looked to innovate its data strategy to handle growing data volumes in the wake of its increasing internationalization and growing data volumes.
The Solution:
RWE launched its strategic Lead in Data (LiD) project that involved creating a sustainable platform for Commercial Analysts to find, access, explore, and visualize data more easily and efficiently. Furthermore, LiD would allow users to tap into the potential of data across the whole enterprise. Overall, these efforts called for the development of a new environment from scratch, as well as the establishment of a new data culture and collaboration means for promoting the sharing of data and insights.
Out of a shortlist of seven vendors, the LiD team adopted Dremio as its solution of choice for the initial proof of concept (PoC); the platform's Data Lakehouse Engine would serve as the underlying platform for providing powerful, direct access to all RWEST data sources and intuitive, self-service analytics environment.
Data from 4 core databases, including Snowflake, is now available for analysis in the LiD Data Lake in an AWS cloud. Databricks prepares and transforms the data from external sources and processes the analysts' models, which can be huge. Serving as the central access system, Dremio also controls access rights and governance. An Alation data catalog ensures visibility into data lineage and relationships and specifies the data sets' owners and data stewards.
"Data literacy and upskilling are very important aspects of the project. With Dremio, the teams are free to choose and they can create the right use cases for all their analytics needs. We are specifically working on building the necessary technical skills. In addition to training programs, which are available both live and on demand, everyone can determine their own personal learning path and pace. There is a community where users can network with peers and a special support team is ready to help with any problems they may encounter."
Nick Plaßmann
Manager at RWE