The Ascend Blog

This week, the team at Ascend is launching our Autonomous Dataflow Service, which enables data engineers to build, scale, and operate continuously optimized, Apache Spark-based pipelines.

The Ascend Platform

Newsroom>Ascend in the News

As we all navigate these uncertain times, one thing has never been more certain — the need to reduce spend. Dollars saved directly equates to employees kept, strategic investments continued, and savings passed on to customers. Finding unnecessary spend and inefficiencies across the business is more important than ever before.

The Ascend Platform

Data scientists and data engineers play the primary role in accelerating a company’s data sophistication, providing both the technology and domain expertise from a sea of zeros and ones into valuable data products. As we reflect on 2019 and look forward to the year and decade ahead, we will examine the evolving nature of these roles and teams.

Data Engineering 101

At Ascend, we are excited to introduce a new paradigm for managing the development lifecycle of data products — Declarative Pipeline Workflows. Keying off the movement toward declarative descriptions in the DevOps community, and leveraging Ascend’s Dataflow Control Plane, Declarative Pipeline Workflows are a powerful tool that allows data engineers to develop, test, and productionize data pipelines with an agility and stability that has so far been lacking in the DataOps world.

The Ascend Platform

Let’s look at how managers of data teams can set the stage for a path that fuels speed and business results, by sorting out different aspects of what needs to get accomplished, and tagging four common mistakes as killer anti-patterns.

Data Engineering 101

In this whitepaper, we compare and contrast both approaches to pipeline orchestration and the impact to data engineering.

Data Engineering 101

Data Engineering 101

While your data team likely includes people with all three of these points of view, what really matters is the position of the leaders, and the pace with which the team is adapting to the real needs of the business. So while we’re rolling the dice with the alphas, let’s take a moment to look at the two sources of value in this context: data and code.

Data Engineering 101

Data Engineers Can Create Continuously Optimized, Apache Spark-Based Pipelines with 85% Less Code

Newsroom>Ascend in the News

Advisors Include Industry Luminaries Microsoft CTO Kevin Scott and Former Sun Microsystems CEO Scott McNealy

Newsroom>Ascend in the News

It is a lesson that Sean Knapp, Founder and CEO at Ascend lives by. I met Sean at his Palo Alto office a few weeks ago, and as we chatted about the state of the market and how industries are shifting towards “as a Service” in almost every aspect, we found ourselves on a track about what really makes a startup successful.

Newsroom>Team Ascend

New capability combines the interactivity of data warehouses with the scale and flexibility of data pipelines for a seamless development experience