September 24, 2022

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I was at the Gartner Data & Analytics conference in London a few weeks ago and wanted to share some thoughts on what I think was interesting, and what I think I learned…

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First, data is in default, and by definition, a liability, as it costs money and has risks associated with it. To turn data into assets, you have to actually do something with it and run the business.

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And the best way to do this is by embedding data, analytics and decisions into business workflows. It can be as simple as making sure you provide people with the information they need right before making a decision.

But Gartner is seeking something a little more sophisticated – for example, what they call decision intelligence, where you go beyond just providing information, and actually help reengineer and optimize decision processes. They say you need data artists who create great questions to complement data scientists looking for great answers.

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And then there are composable applications, which are composed of flexible, reusable modules that help people through multiple steps toward a business outcome, including data, decisions, and actions.

And most of all business people are going to do it themselves, using the latest low code/no code techniques – business technologists, as Gartner calls them, or Citizen Composer. It holds the promise of uncovering more business innovations – letting business people do it themselves more in their area of ​​expertise without the hindrance of IT and technology.

But, of course, it can also mean chaos, so data literacy is important – making sure there is a culture of data, and working to make sure people are asking better questions, not just better answers. Are getting. And that all requires governance, which is done right – not about control, but about competence, about processes, how things should be done.

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And there has been a big change in technology that is supporting all of this. For the longest time, in order to do any analysis, we had to take the data up to the technology — take it out of business applications and move it into a data warehouse or a data lake, or a data lakehouse. The problem is that it’s like cutting a tree out of a forest and trying to grow it somewhere else. It is possible, but it is a lot of hard work. You lose all business context, and have to redo it from scratch, and it can take 80% of the effort.

But now, thanks to the cloud and in-memory, we can bring technology to data. With a decentralized data fabric or data mesh approach, we discard as much of the data as possible, and bring it together whenever needed.

This means we don’t lose all context, and it becomes much easier to incorporate it into business workflows. And it’s not just about analytics – I see data teams embracing technologies like process automation and workflow and chatbots and basic application development to create end-to-end business workflows. And all those functions are now available as services in the cloud, so everything is just a click away.

Overall, data and analytics are coming back where they always should be, and are at the heart of business processes. And that’s great news for companies like SAP, because we’ve been doing intelligent business processes for a long, long time, and we’ve steadily increased intelligence and flexibility as technology advances.

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In fact, Gartner cited examples of combinatorial applications, such as more business-focused decision intelligence and more intelligent product returns, that are being made by customers using the SAP business technology platform right now.

And you don’t have to listen to me for that – many of them have been featured on the sap.com/btp site, or in the latest crop of the SAP Innovation Awards, and you can see all the details of those projects, including There are business problems, benefits, architectural choices and technologies used at sap.com/innovationawards.

Finally: Analytics means business! Talk to us about how to run your business better!

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