GBG Mannheim

Business Intelligence

GBG Mannheim

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Based in Germany, GBG Mannheim is the largest housing association in the federal state of Baden-Württemberg.

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Based in Mannheim, Germany, GBG Mannheim (or rather GBG – Mannheimer Wohnungsbaugesellschaft mbH) is the largest housing association in the German federal state of Baden-Württemberg. With its impressive resume of 19,000 flats, GBG Mannheim accounts for 13% of all flats in the municipality of Mannheim. Needless to say, GBG is a staple of Mannheim life.

Above: A GBG project in Mannheim. Source: GBG.

In addition to providing housing, GBG has other goals for the community. With a history stretching back over 90 years, GBG has been committed to green, urban and sustainable initiatives, be it communal outdoor areas, solar panels on their buildings or affordable housing.

With so many properties and tenants, GBG has a massive influx of data to keep track of contracts, real estate portfolio, service tickets, project information and marketing data. To run an association like theirs efficiently and effectively requires turning that data into insights and decisions on all levels, from strategic long-term vision to operational execution.

Traditionally, GBG used SAP’s own reporting functionalities, as well as Excel and SharePoint, to answer their data questions. To meet growing reporting requirements in the future and to overcome limitations of existing systems, an appropriate solution was sought. For example, Excel evaluations were mostly based on snapshots of data, which made it difficult to analyze historical data in order to identify trends and patterns.

GBG decided to trek into a new era of analytics and business intelligence by implementing an analytics stack that was interconnected, easy to use, scalable and, most importantly, efficient enough to reduce report generation from weeks to days or even hours. For such an ambitious goal, GBG turned to InterWorks.

New Infrastructure for New Insights

When the GBG subsidiary ServiceHaus brought InterWorks into their project, they solidified their goal of updating their analytics stack to the modern era—a goal that InterWorks was more than happy to assist with.

To start, InterWorks decided on a low risk, quick proof of concept where we set up Snowflake and Matillion on the Azure platform, loaded source data from SAP into Snowflake, then connected all that data into Tableau. This allowed ServiceHaus to assess the feasibility of the solution early into the project and laid the foundation for any future developments.

In addition, InterWorks helped ServiceHaus build scalable data loading patterns that leveraged configuration tables, so no advanced data engineering knowledge was required to add additional sources. InterWorks also committed to data privacy being at the core of this build and stayed in line with GDPR and other legal requirements.

Satisfied with the proof of concept, ServiceHaus gave InterWorks the go ahead to fully implement the data stack into their setup and open the door to new heights of data analysis.

Above: Reference architecture for the GBG Mannheim data pipeline.

A Bold New Future with Better, Faster Results

With this updated analytics pipeline, GBG was no longer bound by the limits of their old software. Data that used to be exported to Excel is now available in a central, validated and fast database: Snowflake. This increases on saved time and frees up resources to answer questions with data, instead of wrangling data in Excel spreadsheets.

History tracking in their data insights is also now possible, which can lead to deeper insights into data trends over time that weren’t available before. Adding Tableau to the stack similarly deepened GBG’s analytics capabilities by giving them access to data that was effectively locked up in the SAP ERP system. Tableau’s intuitive interface enables users without any database knowledge to create advanced analytics dashboards that drive decision making.

A modern data stack leads to faster insights and a more agile approach to data analytics. It’s as simple as that. Now, GBG can focus less on data interpretation and more on supporting their tenants, their community and their goal with all that data.



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