Modern Data Platforms for Analytics, Machine Learning, and Generative AI
Challenges of modern data worlds
Many companies today face the challenge of making significant and heterogeneous amounts of data efficiently usable. Different systems, complex SAP and cloud landscapes, as well as high demands on governance and security, make implementation difficult. At the same time, there is increasing pressure not only to test innovative technologies such as artificial intelligence (AI), but also to integrate them productively into day-to-day business.
A data architecture that reduces complexity, breaks down silos, and paves the way for scalable AI applications is all the more critical. This is precisely where we come in, together with Databricks.
Databricks as the Basis for Innovative Data Solutions
Databricks, our new technology partner in the fields of data and AI, provides us with a platform that precisely addresses these requirements and expands our solution portfolio in a targeted manner. Databricks' Lakehouse architecture combines the advantages of a data warehouse, data lake, and AI platform in an open, scalable environment. This creates a uniform database for analytics, machine learning, and generative AI - while reducing complexity in the IT landscape.
Why Databricks? The Most Important Advantages at a Glance
With Databricks is a platform specifically designed for modern Data strategies - open, scalable and completely cloud-native. The most important advantages at a glance:
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Standardized database for analytics and AI
Databricks enables the consolidation of SAP and non-SAP data in a consistent environment. This reduces silos and creates the basis for reliable analyses and automated decisions.
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Fast implementation of use cases
Thanks to ready-made templates, native cloud integration and scalable infrastructure, projects can be started faster and made productive - for example for fraud detection, price optimization or consumption forecasts.
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Future-proof through generative AI
With Mosaic AI offers Databricks an environment for LLM-based applications - including Governance, security and customizability. Companies can use it to implement chatbots, document analysis or decision support, for example.
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Flexibility in the choice of cloud
Databricks runs natively on Microsoft Azure, AWS and Google Cloud. Companies retain the choice of their infrastructure and can continue to use existing cloud services seamlessly.
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Seamless integration into SAP landscapes
Databricks is part of the SAP Business Data Cloud and supports zero-copy sharing and semantic data models. This facilitates integration into existing processes and applications - both in the SAP and non-SAP environment.
This is particularly relevant for companies that have not yet migrated their SAP systems to the public cloud, but already want to work on a future-proof AI architecture: With Databricks, they can establish their data foundation today, implement initial AI use cases and build a scalable platform. This gives them maximum investment security and puts them in the best possible position to move their SAP systems to the cloud in the next step - including an end-to-end data strategy and full SAP AI readiness.
Application Examples: How Companies Use Databricks
The possible uses of Databricks range from Advanced Analytics through to productive AI, with concrete added value for a wide range of industries:
Trade: Dynamic assortment and price optimization based on real-time sales data from SAP and PoS systems.
Financial service provider: Fraud detection in transactions through real-time analysis of large amounts of data, combined with AI-supported pattern recognition.
Utility: Predict energy consumption and network utilization by combining IoT meter data and historical SAP billing data.
Industry & Logistics: Predictive Maintenance through analysis of machine data and spare parts consumption from SAP PM/MM, as well as supply chain optimization along the value chain.
Healthcare & Pharma: Analysis of production, study, and market release data to accelerate approvals and compliance processes, as well as AI-supported prevention analyses in the healthcare context.
Public sector: Transparency about funding programs, spending, and impact by combining operational data and citizen portal information.
These examples demonstrate how Databricks facilitates data integration, Advanced Analytics, and machine learning on a single platform. This enables faster implementation of use cases, reduces complexity in the system landscape, and creates a future-proof architecture for analytics and AI.
What Does This Mean for Your Company?
Our experience in integrating SAP, cloud, and industry-specific processes helps us leverage this potential in a targeted manner and create sustainable added value. For our customers it means:
Faster implementation of data-driven projects: Use cases can be realized more efficiently thanks to the uniform platform.
Less complexity in the system landscape: The integration of different data sources and systems is significantly simplified.
Future-proof architecture for analytics and AI: Companies benefit from a flexible, scalable, and open platform that grows with their requirements.
An example from logistics: Together with a partner, we have completely replaced an on-premise DWH and migrated it to the cloud. Databricks serves as a central data platform there - as the basis for scalable analytics and AI applications along the entire supply chain.
We are also helping energy suppliers to set up an AI platform with Databricks that is specifically geared towards the rapid development and productive use of AI use cases.
Conclusion: Added Value for Your Data Strategy
Databricks complements the Arvato Systems portfolio with a powerful data and AI platform that can be flexibly integrated into existing SAP and cloud landscapes. As an experienced digitalization partner, we support you in optimally integrating Databricks into your system landscape and implementing data-driven projects efficiently and sustainably.
You benefit from modern technology and practical implementation from a single source - with a clear goal: to create real added value from data.
Let's talk. Together we'll find out how Databricks can create real added value in your system landscape - pragmatic, scalable and industry-specific.
Written by
Dr. Alexander Roth is Director of Data & AI at Arvato Systems. With over 15 years of experience, he and his team support companies in maximizing the value of data, automating business processes, and implementing sustainable innovations to drive efficient Digital Transformation.