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Analytics Best Practices: A Business-driven Playbook for Creating Value through

US $24.39
ApproximatelyEUR 21.68
Condition:
Very Good
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Item specifics

Condition
Very Good: A book that has been read and does not look new, but is in excellent condition. No ...
ISBN
9781634628273

About this product

Product Identifiers

Publisher
Technics Publications, LLC
ISBN-10
1634628276
ISBN-13
9781634628273
eBay Product ID (ePID)
24050097179

Product Key Features

Number of Pages
208 Pages
Publication Name
Analytics Best Practices : a Business-Driven PlayBook for Creating Value Through Data Analytics
Language
English
Publication Year
2020
Subject
General
Type
Textbook
Author
Prashanth Southekal
Subject Area
Computers, Business & Economics
Format
Trade Paperback

Dimensions

Item Weight
15.5 Oz
Item Length
9.3 in
Item Width
7.5 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2020-935686
Reviews
"Dr. Southekal proves why he is one of the leading thinkers on data and analytics today. Analytics Best Practices is an indispensable guide for business leaders and those looking to get into the analytics field on the nuances, challenges, and immense opportunities with data." -- Douglas B. LaneyPrincipal, Data & Analytics Strategy, Caserta, and author of Infonomics
Synopsis
Deliver enterprise data analytics success by following Prashanth's prescriptive and practical techniques. Today, organizations across the globe are looking at ways to glean insights from data analytics and make good business decisions. However, not many business enterprises are successful in data analytics. According to Gartner, 80% of analytics programs do not deliver business outcomes. Mckinsey consulting says, less than 20% of the companies have achieved analytics at scale. So, how can a business enterprise avoid analytics failure and deliver business results? This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: Practicality. This book offers prescriptive, superior, and practical guidance. Completeness. This book looks at data analytics holistically across the four key data analytics domains - data management, data engineering, data science, and data visualization. Neutrality. This book is technologically agnostic and looks at analytics concepts without any reference to commercial analytics products and technologies. Dr. Southekal proves why he is one of the leading thinkers on data and analytics today. 'Analytics Best Practices' is an indispensable guide for business leaders and those looking to get into the analytics field on the nuances, challenges, and immense opportunities with data. Douglas B. Laney Principal, Data & Analytics Strategy, Caserta, and author of "Infonomics", Deliver enterprise data analytics success by following Prashanths prescriptive and practical techniques. Today, organizations across the globe are looking at ways to glean insights from data analytics and make good business decisions. However, not many business enterprises are successful in data analytics. According to Gartner, 80% of analytics programs do not deliver business outcomes. Mckinsey consulting says, less than 20% of the companies have achieved analytics at scale. So, how can a business enterprise avoid analytics failure and deliver business results? This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: Practicality. This book offers prescriptive, superior, and practical guidance. Completeness. This book looks at data analytics holistically across the four key data analytics domains - data management, data engineering, data science, and data visualization. Neutrality. This book is technologically agnostic and looks at analytics concepts without any reference to commercial analytics products and technologies.
LC Classification Number
QA76.9.Q36S68 2020

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HPB-Emerald

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