SAP Expands Data Analytics Offerings With New Datasphere, Analytics Cloud Capabilities
With more businesses looking to leverage data generated by SAP systems for analytics and planning tasks, the software giant has added new knowledge graph capabilities to SAP Datasphere, integrated its Joule copilot with the platform, and built new easy-to-use simulation functionality into SAP Analytics Cloud.
SAP continues to expand the capabilities of its SAP Datasphere data warehouse platform and SAP Analytics Cloud system, unveiling new additions and integrations that bring generative AI, data governance and knowledge graph capabilities to the company’s data analytics offerings.
“Data is one of the most important assets that companies use today,” said Daniel Yu, SAP senior vice president of solution management and product marketing, in an interview with CRN. Noting the role data plays in digital transformation initiatives, Yu added: “Data transformation [is] probably the most important priority for a lot of the business and technology leaders that we often talk to.”
Businesses and organizations continue to face challenges in collecting data from operational systems for planning and decision making. Yu noted that SAP applications are a major source of such data.
“Data is still the most important thing. And we want to make sure that we provide insights no matter where the customer’s data resides,” Yu said. “Most of our customers today have data across what we call ‘polycloud’ – multiple clouds, on-prem – and they spend a lot of time and resources extracting and reconstructing all this data again and again.
“And for new technologies like large language models and machine learning, it’s not the size of the data that you really care about, it’s the context of the data that you really need. That is actually more important. It goes beyond just providing more data, it’s about providing the richness of data that is more important.”
To that end SAP unveiled Datasphere Knowledge Graph, a new data modeling capability in Datasphere (in addition to its relational and analytical modeling capabilities) that makes it possible to discover insights and patterns in data across applications and systems. Both technical and business users can better understand relationships between data, metadata and business processes, according to the company, and improve the effectiveness of machine learning systems and large language models.
“It provides a better representation of data, real-world data, across your organization,” Yu said. “It actually captures a better relationship between datasets, between semantic models. And this is important because you can start to ask very deep questions about your business.”
SAP also has integrated its Joule copilot generative AI assistant, which launched in September, with the SAP Analytics Cloud to help automate the creation and development of reports, dashboards, plans and other analytical output. Yu said that makes it easier for people who have line-of-business expertise, but not deep analytical skills, to generate analytical insights from data using a “chat-like experience.”
“It’s very powerful way of actually letting the folks who may not have a very strong background in either analytics or planning to be able to interact with data and research data in a much more powerful way,” he said.
A new capability in SAP Analytics Cloud called “compass” provides a way for business users to run complex, data-driven Monte Carlo simulations using a chat interface to evaluate predictive outcomes for planning and analytics purposes. With compass users can run simulations with many different variables to achieve different predictive outcomes.
SAP also has integrated SAP Analytics Cloud with Datasphere for cross-organizational planning. Businesses can now natively store planning models directly in datasphere and utilize Datasphere as a back-end database or to connect data from multiple sources. “It’s a much more effective way of actually bringing more data with more connections across multiple different data [sources], no matter where the data resides,” Yu said.
Yu noted that all these analytical and planning capabilities are possible only if you have trusted, governed data. SAP announced an expanded partnership with Collibra through which the two companies will work to integrate Collibra’s AI Governance software with data assets in SAP systems, improving data transparency and accountability and ensure compliance with data privacy policies and regulatory requirements.
The new capabilities in SAP Datasphere and SAP Analytics Cloud provide opportunities for partners who engage with clients for data transformation projects within SAP environments, Yu said. That’s particularly true for solution providers that specialize in transforming financial planning, budgeting and simulation processes. The new capabilities also provide partners with opportunities in data governance initiatives.
All of the new capabilities are currently in preview, according to SAP, and there is not yet a firm data for general availability.