Data Observability, Essential for your Modern Data Stack

In this contributed article, Mayank Mehra, head of product management at Modak, shares the importance of incorporating effective data observability practices to equip data and analytics leaders with essential insights into the health of their data stacks. Mayank also explains why this is becoming increasingly paramount, given the current trend towards modern, complex, and distributed data infrastructures.

Largest Data Engineering Survey Reports on Adoption of Modern Data Stack Tools

Airbyte, creators of a fast-growing open-source data integration platform, made available results of the biggest data engineering survey in the market which provides insights into the latest trends, tools, and practices in data engineering – especially adoption of tools in the modern data stack. Its first worldwide State of Data survey displays results in an interactive format so that anyone can drill further into the information using filters to see, for example, adoption patterns by organization size.

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.