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Migrating Data Pipelines from Enterprise Schedulers to Airflow

At Airflow Summit 2021, Unravel’s co-founder and CTO, Shivnath Babu and Hari Nyer, Senior Software Engineer, delivered a talk titled Lessons Learned while Migrating Data Pipelines from Enterprise Schedulers to Airflow. This story, along with the slides and videos included in it, comes from the presentation.

Driving Data Governance and Data Products at ING Bank France

In this episode of Data+AI Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Samir Boualla, CDO at ING Bank France, one of the largest banks in the world. They cover his battlescars in Driving Data Governance Across Business Teams and Building Data Products. At ING Bank France, Samir is the Chief Data Officer. He’s responsible for several teams that govern, develop, and manage data infrastructure and data assets to deliver value to the business.

Spark Troubleshooting, Part 1 - Ten Challenges

“The most difficult thing is finding out why your job is failing, which parameters to change. Most of the time, it’s OOM errors…” Jagat Singh, Quora Spark has become one of the most important tools for processing data – especially non-relational data – and deriving value from it. And Spark serves as a platform for the creation and delivery of analytics, AI, and machine learning applications, among others.

Simplifying Data Management at LinkedIn Part 2

In the second of this two-part episode of Data+AI Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Kapil Surlaker, VP of Engineering and Head of Data at LinkedIn. In part one, they covered LinkedIn’s challenges related to metadata management and data access APIs. This second part dives deep into data quality.

Simplifying Data Management at LinkedIn Part 1

In the first of this two-part episode of Data+AI Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Kapil Surlaker, VP of Engineering and Head of Data at LinkedIn. In this first part, they cover LinkedIn’s challenges related to Metadata Management and Data Access APIs. Part 2 will dive deep into data quality.

Recruiting and Building the Data Science Team at Etsy

In this episode of Data+AI Battlescars (formerly CDO Battlescars), Sandeep Uttamchandani talks to Chu-Cheng, CDO at Etsy. This episode focuses on Chu-Cheng’s battlescars related to recruiting and building a data science team. Chu-Cheng leads the global data organization at Etsy. He’s responsible for data science, AI innovation, machine learning and data infrastructure. Prior to Etsy, Chu-Cheng has led various data roles, including at Amazon, Intuit, Rakuten and eBay.

Jeeves Grows Up: How an AI Chatbot Became Part of Unravel Data

Jeeves is the stereotypical English butler – and an AI chatbot that answers pertinent and important questions about Spark jobs in production. Shivnath Babu, CTO and co-founder of Unravel Data, spoke yesterday at Data + AI Summit, formerly known as Spark Summit, about the evolution of Jeeves, and how the technology has become a key supporting pillar within Unravel Data’s software.

How 84.51°/Kroger Cut Costs and Improved Efficiency with Unravel Data

84.51° is a wholly owned subsidiary of Kroger, the US retailing giant – the largest supermarket chain in America, and the fifth-largest retailer in the world. As an organization, 84.51° is a descendant of dunnhumby, analytics geniuses who revolutionized customer loyalty programs at Tesco in the UK decades ago.

Mastercard Reduces MTTR and Improves Query Processing with Unravel Data

Mastercard is one of the world’s top payment processing platforms, with more than 700 million cards in use worldwide. In the US, nearly 40% of American adults hold a Mastercard-branded card. And the company is going from strength to strength; despite a dip in valuation of more than a third when the pandemic hit, the company has doubled in value three times in the last nine years, recently reaching a market capitalization of more than $350B dollars.