Tom Chavez is the founder and CEO of Superset Inc., a venture studio that founds, funds, and builds technology companies. A serial tech entrepreneur who has spent the last 20 years developing new technologies for data, analytics, and AI, he was CEO and cofounder of Krux, the data management platform acquired by Salesforce in 2016, which is now the technical backbone of Salesforce Marketing Cloud. He holds a PhD in Engineering-Economic Systems and Operations Research from Stanford University and an AB in Computer Science and Philosophy from Harvard University. Chris O'Hara's monthly "Managing the Data" AdExchanger column and annual Econsultancy whitepapers on programmatic media, data management, mobile advertising, and media management are widely read throughout the ad technology, media, and agency industries. Chris joined Krux to build and lead its marketer data practice. He now oversees global product marketing for Salesforce DMP and Data Studio. Vivek Vaidya is a serial tech entrepreneur who has spent the last 25 years building industry-leading technologies in enterprise software, data management, analytics, and machine learning/AI. In his most recent role as CTO of Salesforce Marketing Cloud, he led and managed the engineering teams for all Salesforce Marketing Cloud products. Vivek joined Salesforce in 2016 through the acquisition of Krux, of which he was cofounder and CTO. He has extensive expertise in algorithms, data mining, machine learning technologies, computer networking, distributed systems, and enterprise web application architectures. He holds an MS in Computer Science from the University of Denver and an MS in Mathematics and Computer Applications from the Indian Institute of Technology, Delhi. Visit salesforce.com p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 13.5px Times}p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 13.5px Times; min-height: 16.0px}
Inhaltsangabe
Preface: Origins Introduction: The Magic Coffee Maker Chapter 1: The Emergence of People Data Chapter 2: Three Core Principles for Building a Winning Data Strategy Chapter 3: Data In, Data Out Chapter 4: The Five Sources of Data-Driven Power Chapter 5: Making It Real for Your Organization Chapter 6: The New Basis of Competition: Know, Personalize, and Engage Chapter 7: Seven Forecasts to Light Up Your Future Sensors Acknowlegments Notes Index
Preface: Origins Introduction: The Magic Coffee Maker Chapter 1: The Emergence of People Data Chapter 2: Three Core Principles for Building a Winning Data Strategy Chapter 3: Data In, Data Out Chapter 4: The Five Sources of Data-Driven Power Chapter 5: Making It Real for Your Organization Chapter 6: The New Basis of Competition: Know, Personalize, and Engage Chapter 7: Seven Forecasts to Light Up Your Future Sensors Acknowlegments Notes Index
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