Sign up for our newsletter and get the latest big data news and analysis.

The Powerful Combination of Cloud Data Engineering and Analytics Automation

In this sponsored post, our friends over at Trifacta discuss how unlocking the value from data – whether it is in the cloud or on premises – remains out of reach to many. According to an Alteryx-commissioned survey by YouGov, only 12% of workers reported having the benefit of driving business-changing outcomes through self-service analytics. 

Best Practices in Data Engineering: Brush Up Your Skills and Tidy Your Data with DIY Data

[SPONSORED POST] Trifacta introduces “DIY Data” – a unique webcast series that presents practical aspects of data engineering through hands-on demonstrations.  The series is all about being hands-on with Trifacta through 30-min byte size live and interactive episodes.

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.

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.

Data Con LA 2021 is Coming! Best Regional Data Conference

The Data Con LA schedule is now available and the list contains leaders in various well-hyped industries. Spearheaded by Subash D’Souza and organized and supported by a community of volunteers, sponsors and speakers, Data Con LA features the most vibrant gathering of data and technology enthusiasts in Los Angeles.

The Data Engineering Cloud: Three Lessons for a New Era

In this contributed article, Joe Hellerstein, Co-Founder & CSO and Jeffrey Heer, Co-Founder & CXO, Trifacta, discuss how companies need to think about data engineering and how to democratize it. The more users are able to build and refine data products, the less chance that there will be a breakdown in communication between the people with questions and the people who analyze the data to get answers.

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.