Data Platform

Datacast Episode 132: Big Data Engineering, Data Culture from First Principles, and Reimagined Metadata with Suresh Srinivas

Datacast Episode 132: Big Data Engineering, Data Culture from First Principles, and Reimagined Metadata with Suresh Srinivas

Suresh Srinivas was the Chief Architect of Uber’s data platform, responsible for all data initiatives at the company, including the Databook, Data Quality, and Data Lineage initiatives. Suresh was part of the original team that built Hadoop at Yahoo! and co-founded Hortonworks, which developed and supported open-source software to manage big data and associated processing.

He is leading the OpenMetadata Project to build Metadata APIs & specifications and a single place to discover, collaborate, and get your data right.

Datacast Episode 119: Experimentation Culture, Immutable Data Warehouse, The Data Collaboration Problem, and The Rise of Data Contracts with Chad Sanderson

Datacast Episode 119: Experimentation Culture, Immutable Data Warehouse, The Data Collaboration Problem, and The Rise of Data Contracts with Chad Sanderson

Chad Sanderson was the Product Lead for Convoy's Data Platform team, which includes the data warehouse, streaming, BI & visualization, experimentation, machine learning, and data discovery.

Previously he worked on Microsoft's AI Platform team and led Data initiatives at SEPHORA and Subway. He has built everything from feature stores, experimentation platforms, metrics layers, streaming platforms, analytics tools, data discovery systems, and workflow development platforms.

His love of the data space has also allowed him to implement open-source and SaaS products (early and late-stage) and build cutting-edge technology from the ground up.

Datacast Episode 116: Distributed Databases, Open-Source Standards, and Streaming Data Lakehouse with Vinoth Chandar

Datacast Episode 116: Distributed Databases, Open-Source Standards, and Streaming Data Lakehouse with Vinoth Chandar

Vinoth Chandar is the creator and PMC chair of the Apache Hudi project, a seasoned distributed systems/database engineer, and a dedicated entrepreneur. He has deep experience with databases, distributed systems, and data systems at the planet scale, strengthened through his work at Oracle, Linkedin, Uber, and Confluent.

During his time at Uber, he created Hudi, which pioneered transactional data lakes as we know them today, to solve unique speed and scale needs for Uber’s massive data platform. Most recently, Vinoth founded Onehouse - a cloud-native managed lakehouse to make data lakes easier, faster, and cheaper.

Datacast Episode 101: Scaling Data Engineering, Building Data Teams, and Managed Data Stack with Tarush Aggarwal

Datacast Episode 101: Scaling Data Engineering, Building Data Teams, and Managed Data Stack with Tarush Aggarwal

Tarush Aggarwal is one of the leading experts in leveraging data for exponential growth, with over ten years of experience in the field.

After graduating with a degree in Computer Engineering from Carnegie Mellon in 2011, he became the first data engineer on the analytics team at Salesforce.com. Data was in its infancy, and the log metric framework he built was critical in allowing Salesforce to analyze data across customers and provide benchmarks across different industries and verticals.

Most recently, Tarush led Data for WeWork. WeWork leveraged data to grow 10x in 3 years, supporting a footprint of 800+ offices in 120+ cities in 23+ countries with over 12,000 employees, making WeWork one of the fastest-growing companies in the world. He scaled the data org from 2 to 100+, and their unique approach allowed them to stay lean while supporting every functional area of the business. In 2019, he moved to China to help establish WeWork’s Asia operations and focus on the hyper-growing Chinese market.

Datacast Episode 98: Building Developer Tools, Managing Platform Products, Fostering Diversity, and Enabling Real-Time Data Applications with DeVaris Brown

Datacast Episode 98: Building Developer Tools, Managing Platform Products, Fostering Diversity, and Enabling Real-Time Data Applications with DeVaris Brown

DeVaris Brown is the CEO and co-founder of Meroxa, a VC-backed company enabling teams of any size and level of expertise to build real-time data pipelines in minutes, not months.

Prior to founding Meroxa, DeVaris was a product leader at Twitter, Heroku, VSCO, and Zendesk. When he’s not sitting in front of a computer, you can find DeVaris behind a camera capturing moments in time, at the stove whipping up the finest delicacies, or behind a set of turntables, moving a sea of people through music.

What I Learned From Attending DataOps Unleashed 2021

What I Learned From Attending DataOps Unleashed 2021

Last week, I attended DataOps Unleashed, a great event that examines the emergence of DataOps, CloudOps, AIOps, and other professionals coming together to aggregate conversations around the latest trends and best practices for running, managing, and monitoring data pipelines.

This long-form blog recap dissects content from the session talks that I found most useful from attending the summit. These talks are from DataOps professionals at leading organizations detailing how they establish data predictability, increase reliability, and create economic efficiencies with their data pipelines.

Datacast Episode 50: Reducing Data Downtime with Barr Moses

Datacast Episode 50: Reducing Data Downtime with Barr Moses

Barr Moses is the CEO & co-founder of Monte Carlo, a data reliability company committed to accelerating the world’s data adoption by reducing Data Downtime. Monte Carlo is backed by Accel, GGV, and other top Silicon Valley investors, including the former Chief Data Scientist of the U.S., DJ Patil. Previously, Barr 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, Barr was a management consultant at Bain & Company and a research assistant at the Statistics Department at Stanford. She also served in the Israeli Air Force as a commander of an intelligence data analyst unit and graduated from Stanford University with a B.Sc. in Mathematical and Computational Science.