Unstructured Data Analytics: How to Improve Customer Acquisition, Customer Retention, and Fraud Detection and Prevention
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Turn unstructured data into valuable business insight
Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data. Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions. The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation. Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices.
Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video. These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies. This book provides the baseline knowledge and the practical understanding companies need to put this data to work.
Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence.
You will learn:
From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source. Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage. Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis.
JEAN PAUL ISSON is a recognized worldwide expert and evangelist in Big Data Analytics and Advanced Business Analytics, with over 22 years of experience. He is the author of Win with Advanced Business Analytics and People Analytics in the Era of Big Data.
As Global Vice President of Predictive Analytics & BI at Monster Worldwide Inc. he has built his team from the ground up and successfully conceived and implemented global customer scoring, predictive models and segmentation, machine learning and deep learning solutions, web mining applications, and people analytics solutions for Monster across North America, Europe, and Asia/Pacific. He is also the Founder of the People Analytics Institute.
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