Sign up for our newsletter and get the latest big data news and analysis.

Ascend Creates Automated and Intelligent Dataflows to Power Successful Digital Transformations

Ascend, provider of the Autonomous Dataflow Service, emerged from stealth with $19M in funding to de-risk big data projects and accelerate digital transformations. Ascend operates the only solution with which data engineering teams can quickly build, scale, and operate continuously optimized, Apache Spark-based pipelines. By combining declarative configurations and deep automation, the Ascend Service manages cloud infrastructure, optimizes pipelines, and eliminates maintenance across the entire data lifecycle. Ascend’s unique approach has garnered support from leading venture capital firms, with Accel leading the Series A round with participation from Sequoia Capital, Lightspeed Venture Partners, and 8VC. Technology heavyweights including Kevin Scott, CTO of Microsoft; Scott McNealy, former Sun Microsystems CEO; Maynard Webb, Board Member, Salesforce and Visa; and Deep Nishar, Senior Managing Partner of Softbank Vision Fund, also bring their considerable talents to bear as advisors to the company’s seasoned leadership team

“The market is on the cusp of a new wave,” said Scott McNealy, Ascend advisor and former Sun Microsystems CEO. “The winners of the past decade are those who best leveraged data to fuel their business, yet increased competition necessitates they do more, faster, and with greater efficiency. We’ve seen automation transform every industry and this will be no exception. I have worked with dozens of startups, and it’s rare a company possesses both the experience to define the root of a monumental problem and the talent to do something amazing about it. Ascend is such a company, and their innovation will unequivocally usher in a new era of data engineering.”

“I’ve worked with hundreds of companies over the years and have seen firsthand the challenges encountered with big data and digital transformation,” said Sean Knapp, Founder and CEO of Ascend. “I founded Ascend to fix data pipelines, a critical and ubiquitous component of data architectures that have been neglected until now. By streamlining data pipeline development and automatically optimizing its ongoing performance, we have changed the game for data engineers and the data consumers that depend on them.”

Data pipelines are the lifeblood of every big data project and transformation strategy. Building these pipelines, however, is a time-consuming process for data engineers, requiring fragmented infrastructure and specialized tooling, extensive manual coding, and painful trial and error. Even then, these pipelines become more brittle and prone to failure as data changes, dependencies grow, and the interconnectedness of data movement among systems becomes increasingly complex. As a result, scarce data engineers spend the majority of their time combing through code and logs just to keep everything running, rather than building for new business opportunities. 

The Ascend Autonomous Dataflow Service eliminates these challenges. Its automation and continuous operation of pipelines radically improves data engineering, enabling pipeline creation with 85% less code and reducing the time spent from prototype to production by 90%. Data engineers can now build using declarative configurations and compact code, while the Ascend Dataflow Control Plane automates the management of cloud infrastructure – leveraging its powerful Spark engine to handle massive scale – while perpetually operating and optimizing users’ pipelines in response to inevitable data changes.

Ascend stands to change the perception of big data and AI-driven initiatives by increasing success rates of such projects across industries. While organizations worldwide will spend more than $1.8 trillion annually by 2021 on big data and AI-driven digital transformation efforts (according to Wells Fargo Asset Management researchers), many will struggle to translate those investments into business success. The leading causes, according to many industry researchers, include insufficient resources and expertise to support data initiatives, difficulty accessing siloed data, and an increased urgency for fast analysis and delivery. The Ascend Autonomous Dataflow Service launches into this landscape to address each of those challenges with a compelling new path forward for how businesses unlock value from their big data and AI initiatives far faster and more reliably than the status quo.

“We immediately recognized how big the market opportunity is for Ascend,” said Steve Loughlin, Partner at Accel. “Analytics, AI, and automation are some of the biggest trends we see today, and Ascend is the first to apply such advanced technology to the actual development process that fuels the innovations we hear so much about. The impact Ascend has on the speed of innovation is impressive.”

Ascend’s enormous potential springs from both its groundbreaking technology and its proven leadership team. Prior to founding Ascend, Sean Knapp was co-founder, CTO, and Chief Product Officer at Ooyala where he played key roles in raising $120M, scaling the company to 500 employees, and leading it to a $410M acquisition. Before founding Ooyala, Sean was the technical lead for Google’s legendary Web Search Frontend team, helping to increase Google’s revenues by over $1 billion. Ascend’s Chief Customer Officer, Tom Weeks, has held similar SVP and GM roles at SAP, ThoughtSpot, and Apigee. Anupama Kirpekar, SVP of Engineering, and Steven Parkes, Chief Technology Officer, round out the leadership team and previously held executive positions at HPE, Nimble Storage, NetApp, Twitter, and Square.


Sign up for the free insideBIGDATA newsletter.

Leave a Comment

*

Resource Links: