In this contributed article, Rob Gibbon, Product Manager at Canonical, suggests that data engineers typically know what they need to get done. The problem is that their environment doesn’t always make it easy. If you’re working on premise, it can be hard to get data-intensive solutions off the ground quickly. However, cloud solutions come with lock-in and unpredictable pricing. The game-changer in this scenario is a hybrid solution that will allow you to accelerate data engineering.
Why Accelerating Data Engineering Across Public Clouds and Private Data Centers is a Game Changer
April 15, 2024 by Leave a Comment
Lightning AI Introduces Lightning AI Studios; its Enterprise-Grade Platform for Rapid-prototyping, and Deploying AI Products
December 16, 2023 by Leave a Comment
Lightning AI, the company behind PyTorch Lightning, with over 91 million downloads, announced the introduction of Lightning AI Studios, the culmination of 3 years of research into the next generation development paradigm for the age of AI.
Data Observability, Essential for your Modern Data Stack
August 22, 2023 by Leave a Comment
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
June 14, 2023 by Leave a Comment
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
September 13, 2022 by Leave a Comment
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?
June 28, 2022 by Leave a Comment
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
March 21, 2022 by Leave a Comment
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
January 31, 2022 by Leave a Comment
[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
November 18, 2021 by Leave a Comment
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
November 15, 2021 by Leave a Comment
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.
