2022 Technology Landscape for Self-Service Data

Democratize Data for Technical and Business Users

Every organization today is aspiring to become data-driven! Organizations that are data-driven are 162% more likely to surpass revenue goals and 58% more likely to beat these goals compared to their non-data-driven counterparts.

Most organizations today are data-rich but information-poor.

This is because extracting insights today is bottlenecked by specialized data talent that is required to make data consistent, interpretable, accurate, timely, standardized, and sufficient. One of the key goals of data platform modernization (especially by leveraging the cloud) is to make data self-service for both technical users (data scientists, analysts) as well as business users (marketers, product managers).

While there are 100s of tools and frameworks popping up in a rapidly evolving data landscape, architects and technology leaders find it extremely difficult to navigate the plethora of technologies that are all positioned as the “next silver bullet.”

Teams often get attracted to “shiny new technologies” instead of finding the right fit blocks to make data self-service based on their current use-cases, process, technology, team skills, and data literacy.