To Increase Bandwidth and Support Overburdened Teams, 89% of Data Scientists, Data Engineers, and Enterprise Architects Currently Use or Plan to Adopt Automation, Low-Code, or No-Code Technologies PALO ALTO, Calif. – July 23, 2020 – Ascend.io, the data engineering...
Despite technological innovations in business intelligence (BI), data processing, data warehousing, and other applications, there is still a huge gap in connecting and orchestrating the movement of data between these systems in data pipeline development…
Modern data pipelines run on some of today’s most advanced technologies, yet the process of building, scaling, and maintaining them is as challenging as ever. This is a familiar pattern found across the tech industry, as the innovation focus shifts from raw...
Reposted from: Building a reliable data platform is a neverending task. Even if you have a process that works for you and your business there can be unexpected events that require a change in your platform architecture. In this episode the head of data for Mayvenn...
This TDWI Best Practices Report examines experiences, practices, and technology trends that focus on identifying bottlenecks and latencies in the data’s life cycle, from sourcing and collection to delivery to users, applications, and AI programs for analysis,...
Data scientists and data engineers play the primary role in accelerating a company’s data sophistication
The combination of artificial intelligence and data pipelines opens remarkable new opportunities for data orchestration. The end result is a dynamic, automated paradigm for data movement, one that optimizes speed of delivery and overall accuracy. Bloor Group CEO, Eric...
Reposted from: As data engineers the health of our pipelines is our highest priority. Unfortunately, there are countless ways that our dataflows can break or degrade that have nothing to do with the business logic or data transformations that we write and maintain....
How managers of data teams can set the stage for a path that fuels speed and business results
The current standard for pipeline orchestration relies on engineers to manually translate high-level specs into a set of tasks to be executed on a pre-defined schedule. In advancing orchestration, Ascend opted for a different approach. Taking a page from compilers and...
Data pipelines are a reality for most organizations but they can be operationally brittle. However, it doesn’t have to be that way. Advances in machine learning can take pipeline automation into the realm of intelligent systems. GigaOm analyst, Andrew Brust, and...
The current state of the data world tends to err on solving…
Data teams spend most of their time building ad-hoc software to process the data, most frequently using…
