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The Berner Group
Efficiency In Big Data Management
Holger Frietsch
Can you elaborate on your current role at The Berner Group and your responsibilities in managing big data?
My role in the Berner Group is in the Group IT; I am reporting to the Chief Digital Officer. I am Director Big Data Solutions with the overall responsibility of all data-related matters. We develop and run our central SAP BW data warehouse and provide reporting and dashboarding solutions to 5000+ end users. We are also providing a data analytics platform running on RStudio Server to a currently rather small number of data scientists in the Berner Group. This data analytics platform is connected to the SAP HANA database of our SAP BW and can also include additional or external data sources.
In addition, I am the Data Governance Manager for the Berner Group, defining and executing the Berner Data Governance Program to improve data value, assist in data monetization and use data as a core asset in the company.
Finally, we are responsible for data protection in the whole Berner Group. Based on GDPR, we manage data protection coordinators in all European group companies to assure compliance with data protection rules and laws.
Can you shed light on some of the prominent challenges facing the data management space?
In our company, we currently see the following data-related challenges:
● Data Platform: Upcoming changes and new versions of ERP, SCM, HCM, and CRM software in our company may impact the dispositive data management platform: operational systems also provide analytics capabilities while ignoring the data integration challenges. The architectural guidelines must be defined very early and very clearly.
● Business Layer: Our BI and data platform has evolved over time; business processes and business needs have changed. Data structures are now lacking clear business language and do not fully support business users for ad hoc querying and analytics. Optimization of the business layer in the data platform and usage of a data catalog is required.
● Data Governance: A defined data governance organization is in place, but due to fluctuation and evolvement of processes, data, and systems, both the role model itself and the nomination of people to the roles needs to be updated. Especially we have noticed that the initial target of “one responsible person per data domain” often does not work since some data domains – especially customer and material master data – are too broad and complex for one person. We have adopted your governance model to reflect this.
What are some of the recent business intelligence tools that organizations can leverage to achieve efficient data management?
I think we must distinguish between BI and data management.
Efficient Data Management Requires Easy-To-Use Data Integration Capabilities, Metadata Management, And Scalable Platforms
In the BI area, the need for self service capabilities for end users is still increasing. While there are many tools supporting end users in data reporting and analytics, the best tool cannot overcome bad data structures or insufficient data quality. For self service BI, a clear and understandable business layer of data structures is necessary.
Efficient data management requires easy-to-use data integration capabilities, metadata management, and scalable platforms. In addition, since business process systems like ERP, CRM, HCM etc. often also provide BI and analytics capabilities, a clear data architecture is necessary to avoid data integration back and forth across all these systems.
Are there any similar technologies that you have spearheaded in The Berner Group that can potentially transform the domain?
Our tool landscape includes SAP BW on HANA as our central data platform, SAP Analysis for Office (AfO) for Reporting and Ad-hoc queries and SAP BI Lumira as the IT tool to create dashboards and reporting applications. Since the Excel-based AfO is rather outdated, we have started rollout of SAP Analytics Cloud (SAC) for both reporting/ dashboarding, but mainly for self-service BI.
As an ending note, what is your advice for other senior leaders and CXOs working in the big data space?
Request and expect a clear business strategy to link your data strategy to it and to have a clear fundament for your data strategy. And reasonable, but also achievable data-related use cases are essential to create value from data.
