With this first article of the two-part series on data product strategies, I am presenting some of the emerging themes in data product development and how they inform the prerequisites and foundational capabilities of an Enterprise data platform that would serve as the backbone for developing successful data product strategies.
What do Google’s DevOps Research and Assessment (DORA) and Rollbar have to do with each other? DORA identified four key metrics to measure DevOps performance and identified four levels of DevOps performance from Low to Elite. One way for a team to become an Elite DevOps performer is by focusing on Continuous Code Improvement.
Gartner recognizes Fivetran as the “vendor of choice” for enterprises looking to modernize their data infrastructure.
A true service mesh should focus on how to manage and orchestrate connectivity globally. Connecting a new service mesh for each use case is a much simpler problem to solve, but doing so won’t help you scale. You’ll just be throwing a service mesh in each cluster and calling it a day. The more appealing solution is to stitch together environments.
A revolution is transforming organizations and it's driven by low-code. Using low-code, organizations can quickly build—even in only a few weeks—enterprise applications that would once have taken months to get off the ground. Forrester predicts that by the end of 2021, 75% of development shops will use low-code platforms (up from just 44% in 2020).[1] With that kind of momentum it’s no wonder the low-code market is exploding.
