Applied Business Analytics: : Integrating Business Process, Big Data, and Advanced Analytics / Lin, Nathaniel.

Format:

Book

Author/Creator:

Lin, Nathaniel, author.

Language:

English

Subjects (All):

Information visualization.

Visual analytics.

Big data.

Physical Description:

1 online resource (320 pages)

Edition:

1st edition

Place of Publication:

Pearson, 2014.

System Details:

text file

Summary:

Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll discover why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics… how to become one of those deciders… and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification.

Notes:

Online resource; Title from title page (viewed December 23, 2014)

Includes index.

OCLC:

899528243