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.
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 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.
In a press release delivered today, Unravel Data announced its appearance on CRN’s Big Data 100 list for 2021. Unravel’s entry appears in the Data Management and Integration category. Also featured in this category are other rising stars such as Confluent, Fivetran, Immuta, and Okera, all of whom spoke at new industry conference DataOps Unleashed, held in March.
Cox Automotive is a large, global business. It’s part of Cox Enterprises, a media conglomerate with a strong position in the Fortune 500, and a leader in diversity. Cox also has a strong history of technological innovation, with its core cable television business serving as a leader in the growth and democratization of media over the last several decades.
Let’s start with a real-world example from one of my past machine learning (ML) projects: We were building a customer churn model. “We urgently need an additional feature related to sentiment analysis of the customer support calls.” Creating the data pipeline to extract this dataset took about 4 months! Preparing, building, and scaling the Spark MLlib code took about 1.5-2 months!
Adobe is a legendary Silicon Valley company. From the desktop publishing era of the 1980s, powered by the Adobe Postscript page description language, through the creation and marketing of Photoshop, Illustrator, and other creative power tools, the digital revolution is unthinkable without Adobe.
