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Prophecy.io Launches Low Code Data Engineering SaaS Platform for Spark with $6M investment

Prophecy.io announced the rollout of the new SaaS version of its unique low code data engineering platform, the only solution designed for data practitioners. Prophecy helps businesses accelerate the development and deployment of data pipelines so that massive incoming data streams can be prepared for analytics and machine learning.

Data Engineering Survey: 2021 Impact Report

This Data Engineering Survey: 2021 Impact Report summarizes key findings from the inaugural survey and provides a glimpse into the current and future state of data engineering and DataOps. The report highlights some of the major trends uncovered in this year’s survey including the adoption of cloud data platforms, what platforms are winning (and emerging), what data engineers find to be their biggest challenges, and how organizations are handling sensitive data.

Data Engineering Survey: 2021 Impact Report

This Data Engineering Survey: 2021 Impact Report summarizes key findings from the inaugural survey and provides a glimpse into the current and future state of data engineering and DataOps. The report highlights some of the major trends uncovered in this year’s survey including the adoption of cloud data platforms, what platforms are winning (and emerging), what data engineers find to be their biggest challenges, and how organizations are handling sensitive data.

The Rise of the Data Engineer

In this contributed article, Nir Bar-Lev, CEO of Allegro AI, discusses how organizations that have recognized this need are now moving quickly to restructure their AI teams by introducing Data Engineers into the process; this adjustment gives them a clear advantage over the competition still struggling ‒ and failing ‒ to force their Data Science team to effectively function within their existing IT or R&D organizational structure.

Infographic: Data Engineering Evolved

Ascend.io, the data engineering company, announced results from a new research study about the work conditions of data scientists, data engineers, and enterprise architects in the U.S. Conducted in June 2020, findings from over 300 professionals reveal key insights on their teams’ current workload, productivity bottlenecks, and perspectives on automation and low-code technologies.

Supercharge Data Science Applications with the Intel® Distribution for Python

Intel® Distribution for Python is a distribution of commonly used packages for computation and data intensive domains, such as scientific and engineering computing, big data, and data science. With Intel® Distribution for Python you can supercharge Python applications and speed up core computational packages with this performance-oriented distribution. Professionals who can gain advantage with this product include: machine learning developers, data scientists, numerical and scientific computing developers, and HPC developers.