2022 State of Data Engineering: Emerging Challenges with Data Security & Quality

White Papers > AI > 2022 State of Data Engineering: Emerging Challenges with Data Security & Quality

The 2022 Data Engineering Survey, from our friends over at Immuta, examined the changing landscape of data engineering and operations challenges, tools, and opportunities. The modern data engineering technology market is dynamic, driven by the tectonic shift from on-premise databases and BI tools to modern, cloud-based data platforms built on lakehouse architectures.

More than the on-premises market that preceded it, the cloud data technology market is evolving rapidly, and spans a vast set of open source and commercial data technologies, tools, and products. At the same time, organizations are adopting multiple technologies to keep up with the scale, speed, and use cases that today’s data environment demands. To remain competitive and maximize the value of their data – including sensitive data – organizations are developing DataOps functions and frameworks to varying degrees. DataOps tools and processes enable continuous and automated delivery of data to power BI, analytics, data science, and data-powered products.

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