Moving Towards The Future of Analytics
- By Paul Mah
- June 14, 2023
As the backbone of informed decision-making, data provides a foundation for both businesses and individuals. But what sets business data apart? Rather, why do enterprises invest the effort and resources they do into their data?
Business data
Speaking to CDOTrends, Irfan Khan, the president and chief product officer of SAP Hana Database & Analytics, explained the vital importance of business data using SAP as an analogy. Khan has more than three decades of technology experience under his belt, including an 8-year stint at Sybase as a senior software developer.
“If you are a utility company and you have to create utility bills for your millions of customers and your SAP backend is not available to do that, you are going to be pretty unhappy. So SAP truly is at the core of business functions. And most organizations are using SAP for core business processing. That's the element and the gravity of SAP’s data,” said Irfan Khan.
Fully leveraging the benefits of data is a lot more than digitizing data or setting up a database server, however. Hearing from Khan, enterprises must do their part to break down inevitable data silos. And genuine interoperability can only happen through the establishment of common standards or partnerships.
Understanding the data gap
And data silos are a certainty, given the disparate needs and evolving needs of organizations. Drawing from golf, Khan noted that a budding golfer will end up with a variety of golf clubs based on their initial skills and preferences, and shaped by their growing abilities.
“And that's what goes on in technology, right? A CIO comes in or CTO comes in, they have a preconceived conception about what is good, what are the best tools for the job, and they go and acquire various technologies.”
“Then the next person comes in and the next person comes in, and very quickly, you've got a massively heterogeneous estate. It's never a homogenous one where you have Oracle-only or Microsoft-only data infrastructure. That's a testament of time that everything has to be integrated for it to work.“
This rings true even with a startup starting from a clean slate: “By starting with the current incumbents, the leaders, you might have one homogenized simplified environment. But over time it will certainly decay.” The result? No single vendor will own the entire data stack, says Khan.
This was one of the factors behind the launch of SAP Datasphere, an open data ecosystem for data professionals to easily distribute mission-critical business data across the data landscape. Earlier last month, Google Cloud and SAP announced an expansion of their existing partnership to give enterprises seamless access to their business data from Google’s data cloud – including the training of AI models.
The future of analytics
So where is analytics headed in the future? Khan expects the next stage of self-service analytics to become even more powerful, drawing inspiration from ChatGPT for users to easily access existing data using natural language
“Natural language search has to become a natural extension of analytics. Right now it is too limited to click or look at data in a pivot table – the scope of what you can ask for is already narrowed down at that stage. Conversational AI and conversational analytics will have an incredibly important part to play.“
Finally, Khan sees analytics moving towards greater contextual awareness. He cited the example of a standard search engine query asking about the weather. Typing “what is the weather” into a search box will prompt the search engine to offer to fill in the current location in most instances.
“Analytics will evolve along similar lines. So, it's contextually aware and able to give you a lot more insights around the data,” he said. In this bold new world, the type of analytics could well differ depending on the type of questions asked, the roles and responsibilities of the employee asking, and their credentials.
Paul Mah is the editor of DSAITrends. A former system administrator, programmer, and IT lecturer, he enjoys writing both code and prose. You can reach him at [email protected].
Image credit: iStockphoto/jamesteohart
Paul Mah
Paul Mah is the editor of DSAITrends, where he report on the latest developments in data science and AI. A former system administrator, programmer, and IT lecturer, he enjoys writing both code and prose.