Data is the new oil and a critical differentiator in generating retrospective, interactive, and predictive ML insights. There has been an exponential growth in the amount of data in the form of structured, semi-structured, and unstructured data collected within the enterprise. Harnessing this data today is difficult — typically data in the lakes is not consistent, interpretable, accurate, timely, standardized, or sufficient. Scully et. al. from Google highlight that for implementing ML in production, less than 5% of the effort is spent on the actual ML algorithms. The remaining 95% of the effort is spent on data engineering related to discovering, collecting, preparing data, as well as building and deploying the models in production.
As a result of the complexity, enterprises today are data rich, but insights poor. Gartner predicts that 80% of analytics insights will not deliver business outcomes through 2022. Another study, highlights that 87% of data projects never make it production deployment.
Over the last two years, I have been leading an awesome team in the journey to democratize data at Intuit Quickbooks. The focus has been to radically improve the time it takes to complete the journey map from raw data into insights (defined as time to insight). Our approach has been to systematically break the jou and automate corresponding data engineering patterns, making it self-service for citizen data users. We modernized the data fabric to leverage the cloud, and developed several tools and frameworks as a part of the overall self-serve data platform.
The team has been sharing the automation frameworks both as talks in key conferences and 3 open-source projects. Checkout the list of talks and open-source projects at the end of the blog. It makes me really product on how the team has truly changed the trajectory of the data platform. A huge shoutout and thank you to the team — all of you rock!
In the journey to democratize data platforms, I recently moved to Unravel Data. Today, there is no “one-size-fits-all” requiring enterprises to adopt polyglot datastores and query engines both on-premise as well as the cloud. Configuring and optimizing queries to run seamlessly for performance, SLAs, cost, and root-cause diagnosis is highly non-trivial requiring deep understanding. Data users such as data analysts, scientists and data citizens essentially need a turn-key solution to analyze and automatically configure their jobs and applications.
I am very excited to be joining the Unravel Data driving the technology of AI-powered data operations platform for performance management, resource and cost optimization, and cloud operations and migration. The mission to democratize data platforms continues …
The full press release can be viewed below.
Unravel Hires Data Industry Leader with over 40 Patents as New Chief Data Officer and VP of Engineering
The new CDO will draw on experience from IBM, VMware and Intuit QuickBooks to help Unravel customers accelerate their modern data workloads
PALO ALTO, CALIFORNIA – April 1, 2020 – Unravel Data, the only data operations platform providing full-stack visibility and AI-powered recommendations to drive more reliable performance in modern data applications, today announced that it has hired Sandeep Uttamchandani as its new Chief Data Officer and VP of Engineering. Uttamchandani will help boost Unravel’s capabilities for optimizing data apps and end-to-end data pipelines, with special focus on driving innovations for cloud and machine learning workloads. He will also lead and expand the company’s world-class data and engineering team.
Uttamchandani brings over 20 years of critical industry experience in building enterprise software and running petabyte-scale data platforms for analytics and artificial intelligence. He most recently served as Chief Data Architect and Global Head of Data and AI at Intuit QuickBooks, where he led the transformation of the data platform used to power transactional databases, data analytics and ML products. Before that, he held engineering leadership roles for over 16 years at IBM and VMWare. Uttamchandani has spent his career delivering innovations that provide tangible business value for customers.
“We’re thrilled to have someone with Sandeep’s track record on board the Unravel team. Sandeep has led critical big data, AI and ML efforts at some of the world’s biggest and most successful tech companies. He’s thrived everywhere he’s gone,” said Kunal Agarwal, CEO, Unravel Data. “Sandeep will make an immediate impact and help advance Unravel’s mission to radically simplify the way businesses understand and optimize the performance of their modern data applications and data pipelines, whether they’re on-premises, in the cloud or in a hybrid setting. He’s the perfect fit to lead Unravel’s data and engineering team in 2020 and beyond.”
In addition to his achievements at Intuit QuickBooks, IBM and VMWare, Uttamchandani has also led outside the office. He has received 42 total patents involving systems management, virtualization platforms, and data and storage systems, and has written 25 conference publications, including an upcoming O’Reilly Media book on self-service data strategies. Uttamchandani earned a Ph.D. in computer science from the University of Illinois at Urbana-Champaign, one of the top computer science programs in the world. He currently serves as co-Chair of Gartner’s CDO Executive Summit.
“My career has always been focused on developing customer-centric solutions that foster a data-driven culture, and this experience has made me uniquely prepared for this new role at Unravel. I’m excited to help organizations boost their businesses by getting the most out of their modern data workloads,” said Sandeep Uttamchandani, CDO and VP of Engineering, Unravel Data. “In addition to driving product innovations and leading the data and engineering team, I look forward to collaborating directly with customer CDOs to assist them in bypassing any roadblocks they face in democratizing data platforms within the enterprise.”
About Unravel Data
Unravel radically simplifies the way businesses understand and optimize the performance of their modern data applications – and the complex pipelines that power those applications. Providing a unified view across the entire stack, Unravel’s data operations platform leverages AI, machine learning, and advanced analytics to offer actionable recommendations and automation for tuning, troubleshooting, and improving performance – both today and tomorrow. By operationalizing how you do data, Unravel’s solutions support modern big data leaders, including Kaiser Permanente, Adobe, Deutsche Bank, Wayfair, and Neustar. The company is headquartered in Palo Alto, California, and is backed by Menlo Ventures, GGV Capital, M12, Point72 Ventures, Harmony Partners, Data Elite Ventures, and Jyoti Bansal. To learn more, visit unraveldata.com.
The name Unravel Data is a trademark of Unravel Data™. Other trade names used in this document are the properties of their respective owners.
Jordan Tewell, 10Fold