SAP and Databricks: Unlocking a New Era of Business AI with Open Data

By Jorge Garcia

 


Just a few days ago, SAP announced a strategic partnership with Databricks, signaling a bold step towards a more open and AI-driven future for enterprise data management.

According to both companies, this collaboration aims to break traditional data silos by enabling seamless integration between SAP Business Data Cloud and Databricks' AI and analytics capabilities.

The goal?

To empower businesses with more agile, intelligent, and efficient AI-driven decision-making.


A Unified Data Landscape

At the heart of this partnership is SAP’s Business Data Cloud, a new platform designed to unify data across various SAP and non-SAP systems.

By integrating with Databricks' AI and machine learning (ML) ecosystem, SAP aims at providing enterprises with enhanced capabilities to analyze, process, and utilize their data more effectively.

This means businesses can tap into the full potential of their enterprise data without complex data extraction and movement processes.

In the words of SAP CEO Christian Klein:

“SAP Business Data Cloud unleashes the full value of enterprise data for Business AI.  It combines SAP’s unique expertise in mission-critical, end-to-end processes and semantically rich data with Databricks’ world-class data engineering capabilities to create a ground-breaking solution that helps organizations do more with their data than ever before.”

Turbocharging Business AI

One of the aspects that standout about this partnership is the potential ability to accelerate AI-driven business solutions. 
By taking advantage of Databricks' robust data lakehouse architecture, organizations using SAP solutions can enhance their predictive analytics, automate workflows, and thus improve real-time insights.
This integration also aims to simplify access to AI models, reducing time-to-value for AI-driven innovations in industries like finance, manufacturing, and supply chain management.

Embracing an Open Ecosystem

A key highlight of SAP’s approach is its commitment to openness.
Unlike traditional proprietary systems that lock data within walled gardens, SAP Business Data Cloud enables businesses to maintain full control over their data while taking advantage of external AI and analytics platforms.
The approach aims to ensure flexibility, scalability, and compliance with evolving regulatory requirements, giving enterprises the best of both worlds: security and innovation.


So… What?

The SAP-Databricks partnership marks a significant shift in enterprise AI and data management.
By fostering an open, collaborative ecosystem, SAP is making it easier for businesses to harness the power of AI while maintaining control over their data. As enterprises increasingly look to AI for competitive advantage, this collaboration provides a solid foundation for innovation, efficiency, and smarter decision-making in the years ahead.
The future of enterprise data is not just about storage—it is about intelligence, and both SAP and Databricks are making sure their customers are well-equipped for what is next. 
An interesting partnership to keep following further.


Disclaimer: SAP® and Databricks® are registered trademarks of their respective owners. This post is for informational purposes only and is not affiliated with, endorsed by, or sponsored by SAP SE, Databricks, or any of their subsidiaries or affiliates.


Comments

Post a Comment

Popular posts from this blog

Machine Learning and Cognitive Systems, Part 2: Big Data Analytics

By Jorge Garcia
Image
In the first part of this series, I described a bit of what machine learning is and its potential to become a mainstream technology in the industry of enterprise software, and serve as the basis for many other advances in the incorporation of other technologies related to artificial intelligence and cognitive computing. I also mentioned briefly how machine language is becoming increasingly important for many companies in the business intelligence and analytics industry. In this post I will discuss further the importance that machine learning already has and can have in the analytics ecosystem, especially from a Big Data perspective. Machine learning in the context of BI and Big Data analytics Just as in the lab, and other areas, one of the reasons why machine learning became extremely important and useful in enterprise software is its potential to deal not just with huge amounts of data and extract knowledge from it—which can somehow be addressed with disciplines such as data ...
Read more

So, WTF is Artificial Intelligence Anyway?

By Jorge Garcia
Image
Image By Seanbatty (Pixabay) According to Encyclopedia Britannica , artificial intelligence (AI) can be defined as: "The ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, like the ability to reason, discover meaning, generalize, or learn from previous experiences." By now, we have all heard about how AI can make it possible for computers, machines and other electronic devices to perform increasingly complex and human-like tasks. As all this sounds almost like magic, with machines performing increasingly complex tasks —from new gaming computers to self-driving cars – in reality most of AI technologies rely on the blend of software methods and technologies that imply collecting, processing and recognizing patterns within large amounts of data. So, how does AI W...
Read more

Teradata Open its Data Lake Management Strategy with Kylo: Literally

By
Image
Still distilling good results from the acquisition of former consultancy company Think Big Analytics , Teradata , a powerhouse in the data management market took one step further to expand its data management stack and to make an interesting contribution to the open source community. Fully developed by the team at Think Big Analytics, in March of 2017 the company launched Kylo –a full data lake management solution– but with an interesting twist: as a contribution to the open source community. Offered as an open source project under the Apache 2.0 license Kylo is, according to Teradata, a new enterprise-ready data lake management platform that enables self-service data ingestion and preparation, as well the necessary functionality for managing metadata, governance and security. One appealing aspect of Kylo is it was developed over an eight year period, as the result of number of internal projects with Fortune 1000 customers which has enabled Teradata to incorporate several be...
Read more