From BO, Lumira, Design Studio, BW/4HANA, HANA Cloud, SAP Analytics Cloud, SAC, Data Intelligence, on-prem to cloud transition, unclear AI/ML tooling - the journey has been challenging for SAP customers globally. Even today, customers have little to show in terms of value to business.

'Data Stack' in confusing enough and the 'Modern Data Stack' is muddling waters even more. With operational AI/ML now accessible, advanced use-cases are better managed with the (always) latest predictive tools, and SAP is only playing catch-up.

Geo-political, environmental, regulatory, currency, supply chains, wars, pandemics, and other issues are here to stay. For example, a currency might depreciate by 50% in a day. Do you think embarking on lengthy data analytics projects frequently really practical? In most organizations data analytics has become an end in itself, incapable of supporting operational data driven decision making.

Creating a proof-of-concept initiative to test the applicability of more advanced governance styles in your environment, evaluate the business outcomes and value, emerging risks, technological limitations, and cultural barriers to wider adoption is often impossible with the current approach. Even if a vendor is brave enough to offer a POC, time frames and costs are truly impractical.

Most existing data integration tools are limited in their ability to collect and analyze all forms of metadata to provide actionable insights to support automation. As a result, data teams often never move to the value generation phase, stuck in an endless battle with just getting data meaningfully together. Sounds familiar?

Data Analytics is witnessing an unprecedented rate of change, and with it, a massive amount of hype. At the same time, competent talent with operational skills are in such short supply, that staffing itself is impossible. And this problem is not going away soon.