DEMO: Conversational Analytics with SAP Analytics Cloud in Business Data Cloud

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Today’s business moves fast. And to keep up, we need to make decisions quickly and with confidence. But even in data-rich organizations, that’s not always easy, too often the insights people need are locked behind tools, dashboards, or technical expertise. Despite heavy investment in analytics, many business analysts and decision-makers still struggle to access the right data at the right time. They may know what they need, but not where to find it, or how to get it fast enough.

That’s the problem conversational analytics solve, thanks to generative AI, business analysts and all decision-makers can now ask questions in plain language. Like “Show me actuals versus forecast by region.” And instantly, they get clear, contextual insights, no delays.

Watch a demo of conversational analytics with SAC in BDC

In this video, first, we demonstrate the just ask feature for natural language queries. With the just ask NLQ feature in SAP Analytics Cloud, business analysts can ask questions in plain language.
Then we demonstrate analytical insights in the Joule AI copilot. Joule takes the NLQ experience to next level, with a real conversational analytics experience for all business users, right where they work, no switching tools.
The result is faster decisions, higher productivity, and a culture where using data becomes effortless and automatic.

Recommended Resources

Blog Post: Conversational analytics: Why rich metadata and business semantics matter more than ever

Blog Post: SAP Business Data Cloud for the Business Analyst: turning raw data to trusted and actionable insight

Hands-on: SAP Business Data Cloud basic trial

[venkatamandavilli]

@ThierryAudas 

This demo is a great example of how conversational analytics makes SAC more accessible for business users. I like that the video shows the "Just Ask" natural language query feature in action, because that is where the value really shows up for people who do not want to build formulas or complex reports. It feels especially relevant for teams that want users to explore data on their own while still getting trustworthy, visual answers.

[ThierryAudas]

Great feedback, thank you @venkatamandavilli.  I started a discussion on this topic, let me know your thoughts: NLQ in the real world: what metadata setup made it successful for you?