Presented by SAP

The old adage that time is money will always ring true.

But modern businesses leaders might update the quote to say that time is value. That is, the faster a company can react to a business event, the more value it derives for itself and its customers.

Dr. Richard Hackathorn, an expert in analytics, business intelligence and data warehousing neatly describes this phenomenon with a simple example: a customer request for product information. A company can provide this information in seconds, minutes, hours or days. Clearly, there is more value in a quicker response. He notes that the longer the delay, or latency of the response, the less business value accrues to the company.

This latency – caused by the time it takes to capture data, analyze it and make a decision – is where companies can derive the most value vis a vis time.

The goal for businesses is to reduce these times to near zero, leveraging agentic AI and high-quality data to uncover transformative insights. While this objective is increasingly achievable, most companies are not yet there.

That’s because many organizations grapple with data they cannot trust. In a global survey of 1,200 business and technology leaders, 55% cited poor data quality as their biggest challenge. And nearly half struggle to harmonize data across multiple ecosystems.

A business data fabric reduces latency and powers advanced AI

The root cause of these challenges is fragmented data, which leads to uneven AI outcomes, slow decision-making and a disconnect between business applications. Managing data across different platforms can be costly and complex, especially when the data lacks necessary context for collaborative insights.

One of the most important ways data can close that latency gap is by informing and enriching organizations' AI efforts. To leverage AI effectively, organizations must first have the right data foundation. Without context, AI applications cannot deliver meaningful insights, and business users are left without domain-specific knowledge. Prioritizing business semantics, data literacy and self-service capabilities is essential for maximizing data utility.

A business data fabric addresses these needs and reduces latency by providing an integrated, semantically-rich data layer over fragmented data landscapes. This architecture offers seamless access to trusted data, ensuring accurate decisions, real-time insights and simplified data management. It creates a single source of truth, enabling agile self-service access and comprehensive data governance.

SAP Business Data Cloud and Databricks

SAP Business Data Cloud (SAP BDC) is a fully managed SaaS solution designed to reduce latency and bridge the trust gap by harmonizing data to generate intelligent insights and power AI. SAP BDC is the next evolution of our Business Data Fabric strategy. It accelerates a company’s ability to ingest trusted data from any source -- while keeping its business context intact -- and make it actionable for every business user by powering intelligent apps, planning, AI and advanced analytics.

Our partnership with Databricks takes these capabilities even further and makes their industry-leading AI/ML, data science and data engineering capabilities natively available within SAP BDC. This means it’s easier for companies to combine semantically rich, business-ready data from SAP applications and other business applications. Databricks’ zero-copy Delta Sharing protocols make it faster and easier for companies to seamlessly integrate unstructured data from any source with data from SAP applications into a single, harmonized data model.

Real business impact

Henkel is a multinational company that manufactures everything from industrial adhesives to laundry detergents. With a legacy of more than 145 years and leading market positions worldwide, Henkel has been a long-standing SAP customer – and relies on SAP as the cornerstone of its data strategy. SAP Business Data Cloud will help Henkel further unlock the value of data within SAP applications and systems, and drive future product innovation and agility to changing market conditions.

Moreover, Henkel is a customer of both SAP and Databricks. Databricks has been its central data lakehouse for years, which has enabled it to build sophisticated data products, from financial analytics to inventory management. With the new SAP Databricks solution, Henkel’s day-to-day data management and AI development tasks can maintain a constant connection to the company’s latest business data.

All this is to say: SAP BDC and its deep Databricks integration will help Henkel close existing trust gaps and decrease the latency involved with complex data processing, delivering even more value to both Henkel and its customers.

Meeting today’s data and AI opportunities

Back in 2004, Dr. Hackathorn was already grappling with how data technology advances could reduce companies’ time to value. He said, “The key concept behind real time [data] is that our artificial representation must be in sync with the real world so that we can respond to events in an effective manner.”

Over 20 years later, data, analytics and AI technologies have evolved to bring this vision to life. With solutions like BDC, enterprises can finally enact a data strategy using a reliable data foundation enabling them to stay ahead in a competitive, fast-evolving global market.

Irfan Khan is chief product officer for SAP Data & Analytics, SAP

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