DataOps Unleashed is the first-ever event for the global DataOps community.
We came together on Wednesday, March 17th, 2021 for DataOps Unleashed – a gathering of DataOps, CloudOps, AIOps, MLOps, and data-oriented DevOps professionals, including all data team members and their management, up to the CDO level. We shared the latest trends and best practices for running, managing, and monitoring data pipelines and data-intensive analytics workloads.
The event was a tremendous success, with thousands of registrants, presentations by many leaders in DataOps, and lively discussion as to how we are all working together to make data-driven applications and analytics work better.
Session recordings are available in two places:
1. Stay on this page for most Main Stage sessions, and breakout sessions featuring Unravel Data speakers.
2. For breakout sessions, including sponsored and vendor-specific sessions, visit the dedicated DataOps Unleashed website.
Key: (CS) = case study
DataOps innovator Kunal Agarwal, CEO of Unravel Data, describes how companies large and small are using DataOps to make their technology stacks hum, get more done at a lower cost, and improve both customer experience and the bottom line.
Kevin Davis shares the catalysts that started Adobe on their journey in moving petabytes of data to the cloud, the processes being employed to ensure key customer challenges are addressed in the new environment, and other tools and strategies that are helping along the way.
James Fielder, Senior Data Engineer at Cox Automotive, shows how a small data team manages DataOps for his organization’s global footprint, highlighting their use of Databricks on Microsoft Azure.
This talk demystifies the new data stack that thousands of companies are deploying to convert data into insights continuously and with high agility. Session presented by Shivnath Babu, Co-Founder and CTO at Unravel Data.
Angelo Carvalho, Principal Solutions Architect at AWS, reviews best practices and new features that enable you to cut operating costs and create efficiencies when processing vast amounts of data using Amazon EMR.
What is DataOps? A methodology for building pipelines? A set of development and execution tools? Or a process for continuous improvement? This session helps us better understand our DataOps efforts as they evolve.
This talk, from Sandeep Uttamchandani, author of The Self-Service Data Roadmap, describes how building checkpoints into the DataOps loop can reduce missed SLAs, cost outages, and escalations from data users, while avoiding data pipeline surprises.
Hear from 84.51°, a division of retail giant Kroger, as they share how they used Unravel Data, Yarn, Impala, and a DataOps approach to solve challenges associated with small files and fix big data pipelines.
Senior engineers Chinmay Sagade and Srinivasa Gajula show how Mastercard used Unravel Data to create an application monitoring system for detecting harmful workloads and meeting SLAs around resiliency and latency.
Wayne Eckerson of Eckerson Group convenes Unravel Data’s Kunal Agarwal, Astronomer's Ry Walker, DataKitchen's Christopher Bergh, Immuta's Matthew Carrol, and Starburst's Justin Borgman to discuss DataOps.