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Defining Enterprise Data and Analytics Strategy: Pragmatic Guidance on Defining Strategy Based on Successful Digital Transformation Experience of ... Companies (Management for Professionals) Papeback -
by Prakash Sah
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Details
- Title Defining Enterprise Data and Analytics Strategy: Pragmatic Guidance on Defining Strategy Based on Successful Digital Transformation Experience of ... Companies (Management for Professionals)
- Author Prakash Sah
- Binding Papeback
- Condition New
- Pages 174
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date pp. 192
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # 6398548800
- ISBN 9789811957215 / 9811957215
- Weight 0.61 lbs (0.28 kg)
- Dimensions 9.21 x 6.14 x 0.41 in (23.39 x 15.60 x 1.04 cm)
- Category Business / Economics / Finance
- Quantity available 4
About Cold Books New York, United States
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From the publisher
From the rear cover
This book describes key elements of enterprise data and analytics strategy and prescribes a pragmatic approach to define strategy for large enterprises. It is based on successful digital transformation experience of multiple Fortune 500 and other large enterprises. It is estimated that more than 50% of data and analytics initiatives fail globally because of inherent complexities of such initiatives. The book discusses key challenges that enterprises struggle with, such as--defining enterprise data and analytics strategy, and key elements that should be considered while doing so; limitations of one-size-fits-all approach which does not work for all enterprises; aligning data and analytics initiative with business strategy of the CEO; establishing a futuristic technology and architecture foundation, given the exponential rate of innovation in data and analytics technologies; defining the right data and analytics organization model and structure; reasons why data and analytics organization and processes need to be different from other functions; managing organizational change to ensure success of data and analytics initiative; defining a business value measurement framework and calculating ROI from data and analytics initiative; and key skills required in a data and analytics leader to wade through political and other challenges of a large enterprise.
Often, data and analytics leaders define a strategy that is focused primarily on technology and architecture. This leads to failure of a majority of data and analytics initiatives across enterprises. The book recommends defining a holistic strategy through five key elements - (a) business capabilities, (b) technology and architecture, (c) team, processes, and governance, (d) organizational change management, and (e) value measurement framework.
The book helps executives, chief digital/analytics officers, data and analytics professionals, consultants, and students in addressing various challenges and dilemmas that they face every day to make their enterprises more data driven
