Fr. 80.00

Embedded Analytics - Integrating Analysis with the Business Workflow

English · Paperback / Softback

Shipping usually within 3 to 5 weeks

Description

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Over the past 10 years, data analytics and data visualization have become essential components of an enterprise information strategy. And yet, the adoption of data analytics has remained remarkably static, reaching no more than 30% of potential users. This book explores the most important techniques for taking that adoption further: embedding analytics into the workflow of our everyday operations. Authors Donald Farmer and Jim Horbury show business users how to improve decision making without becoming analytics specialists. You'll explore different techniques for exchanging data, insights, and events between analytics platforms and hosting applications. You'll also examine issues including data governance and regulatory compliance and learn best practices for deploying and managing embedded analytics at scale. --

About the author










Donald Farmer is the Principal of TreeHive Strategy, a strategic advisory practice specializing in data, analytics and innovation strategy. His background is very diverse, with over 30 years of deeply practical experience in industries ranging from fish-farming to archaeology to advanced manufacturing. He has worked in award-winning startups in the UK and Iceland, and spent 15 years at Microsoft and at Qlik leading teams designing and developing new enterprise capabilities in data integration, data mining, self-service analytics and visualization. Donald Farmer is an advisor to investors, venture funds, incubators and startups around the world. He mentors executives and speaks globally at events and private workshops. Donald lives with his wife, Alison, an artist, in a recycled-polystyrene house near Seattle with one of the world's most beautiful treehouses - the tree hive - in their wild garden.

Product details

Authors Donald Farmer, Farmer Donald, Jim Horbury
Publisher O'Reilly
 
Languages English
Product format Paperback / Softback
Released 31.05.2023
 
EAN 9781098120931
ISBN 978-1-09-812093-1
Dimensions 178 mm x 232 mm x 10 mm
Weight 298 g
Subjects Natural sciences, medicine, IT, technology > IT, data processing > IT

machine learning, COMPUTERS / Data Science / Machine Learning

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