A couple things happened that helped shape the current data landscape. Enterprises began to move more of their on-premise workloads to the cloud. Modern data stack vendors offered managed services as composable cloud offerings that could offer customers more reliability, better flexibility of their systems and the convenience of on-demand scaling.

But as companies barreled through the zero interest rate policy (ZIRP) period and expanded their number of data tooling vendors, cracks started to emerge in the MDS facade. Issues of system complexity (brought on by many disparate tools), integration challenges (numerous different point solutions that need to talk to each other) and underutilized cloud services left some wondering whether the promise of the MDS panacea would be achieved.

Many Fortune 500 companies had invested heavily in data infrastructure without a clear strategy for how to generate value from that data (remember, finding insights is hard!), leading to inflated costs without proportional value. But it was trendy to collect various tools — one would often hear reports of multiple overlapping tools being used by different teams at the same company. Across business intelligence (BI) for instance, many companies would have Tableau, Looker and perhaps even a third tool installed that essentially served the same business purpose while racking up bills three times as fast.