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How to Optimize the Modern Data Stack with Enterprise Data Observability

In this sponsored post, our friends over at Acceldata examine how in their attempt to overcome various challenges and optimize for data success, organizations across all stages of the data journey are turning to data observability where they can get a continuous, comprehensive, and multidimensional view into all enterprise data activity. It’s a critical aspect of optimizing the modern data stack, as we’ll see. 

What Is Data Reliability Engineering?

In this contributed article, Kyle Kirwan, CEO and co-founder of Bigeye, discusses Data Reliability Engineering (DRE), the work done to keep data pipelines delivering fresh and high-quality input data to the users and applications that depend on them. The goal of DRE is to allow for iteration on data infrastructure, the logical data model, etc. as quickly as possible, while—and this is the key part! —still guaranteeing that the data is usable for the applications that depend on it.

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.