SF Bay Area

Arvind Prabhakar | CPO & Co-founder | StreamSets
Welcome Speaker

Arvind Prabhakar is a seasoned technology leader, who has worked on data integration challenges for over 10 years. Before co-founding StreamSets, Arvind was an early employee of Cloudera, and led teams working on integration technologies such as Flume and Sqoop. A member of the Apache Software Foundation, Arvind is heavily involved in the open-source community as the PMC Chair for Apache Flume, the first PMC Chair of Apache Sqoop, and member of various other Apache projects. Prior to Cloudera, Arvind was a software architect at Informatica, where he was responsible for architecting, designing, and implementing several core systems.

Session Title: Lifting the Lid on the Hidden Data Problem
Session Abstract: This session will unveil new research uncovering the hidden data problems faced by data practitioners and decision makers. Learn what your peers are saying about data friction putting the brakes on innovation and taking control of the data “wild west” while empowering lines of business.

Barr Moses | Monte Carlo | CEO & Co-founder
Executive Fireside Chat Speaker

Barr Moses is CEO & Co-Founder of Monte Carlo, a data reliability company and creator of the data observability category, backed by Accel, GGV, Redpoint, ICONIQ Growth, Salesforce Ventures, IVP, and other top Silicon Valley investors. Previously, she was VP Customer Operations at customer success company Gainsight, where she helped scale the company 10x in revenue and, among other functions, built the data/analytics team. Prior to that, she was a management consultant at Bain & Company and a research assistant at the Statistics Department at Stanford University. She also served in the Israeli Air Force as a commander of an intelligence data analyst unit. Barr graduated from Stanford with a B.Sc. in Mathematical and Computational Science.

Session Title: How to Measure ROI for Your Data Platform
Session Abstract: Your team just migrated to a data mesh (or so they think). Your CTO is all in on this “modern data stack,” or as she calls it: “The Enterprise Data Discovery.” To satisfy your company’s insatiable appetite for data, you may even be building a complex, multi-layered data ecosystem: in other words, a data platform. Still, it’s one thing to build a data platform, but how do you ensure it actually drives value for your business? In this fireside chat, Barr Moses, CEO & co-founder of Monte Carlo, will share why best in class data teams are treating data platforms like a product to optimize ROI on this critical investment with reliability and scalability in mind.

Jon Hsieh | Bigeye | Product Manager
Keynote Speaker

Jonathan is a Product Manager at Bigeye, the industry-leading data observability platform, responsible for its alert to resolution experiences and its data science-driven anomaly detection efforts. Before starting at Bigeye, Jonathan was the Director of Product Management for Data Management at Cloudera, where he drove cloud adoption, data governance, and the lineage capabilities that connected the lineage of ingest, ETL, and ML services. This was preceded with 10 years of experience building a deep understanding of data processing, storage and analysis as an principal engineer, tech lead, and engineering manager. He led the Engineering Infrastructure team, the Apache HBase Team, and was a founder of the Apache Flume project. Jonathan has an M.S. in Computer Science from University of Washington and also has an M.S. and a B.S. in Electrical and Computer Engineering from Carnegie Mellon University.

Session Title: Why the Buzz Around Data Mesh, Data-as-a-Product, and Data Contracts?
Session Abstract: Today’s hybrid and cloud datalakes and cloud data warehouses have created a secular shift in the data world. The simplification of systems problems has unleashed a new wave of fragmentation, unbundling, and heterogeneity around the data stack. What used to be a world with monolithic data infrastructure, is now moving towards one with federated data ownership and interdependent data pipelines. The true value of data comes when different data sets are combined to create new insights but these shifts add complexity and make “data nirvana” harder to achieve.

This new complexity begs for solutions to tackle these problems. Interestingly, the industry has seen a similar story with the rise of the public cloud in the software engineering world. We’ll compare stories by exploring the similarities, and more interestingly the differences in areas like reliability engineering, integration, and observability.

There is no fee to attend the Connected Enterprise Forum but space is limited. All requests will be reviewed and a response email will be sent within 24 hours. Not everyone will be accepted to attend.