Big Data for Managers: Creating Value

✍ Scribed by Atal Malviya; Mike Malmgren

• Publisher: Routledge
• Year: 2019
• Tongue: English
• Leaves: 175
• Category: Library

✦ Synopsis

In today's fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information. Correctly used it has the power to create sustainable value in different forms for businesses. The commonly used term for this data is Big Data, which includes structured, unstructured and hybrid structured data. However, Big Data is of limited value unless insightful information can be extracted from the sources of data.

The solution is Big Data analytics, and how managers and executives can capture value from this vast resource of information and insights. This book develops a simple framework and a non-technical approach to help the reader understand, digest and analyze data, and produce meaningful analytics to make informed decisions. It will support value creation within businesses, from customer care to product innovation, from sales and marketing to operational performance.

The authors provide multiple case studies on global industries and business units, chapter summaries and discussion questions for the reader to consider and explore. Big Data for Managers also presents small cases and challenges for the reader to work on - making this a thorough and practical guide for students and managers.

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Dedication
Table of Contents
Acknowledgements
Foreword
1. Introduction
For the practising manager
A non-technical book
Structure of the book
2. Big Data revolution
Data driven decisions and value creation
History of data and Big Data
Data and analysis
Data analysis and statistics
Data analysis and computing
Advances in collection mechanisms
Relational databases
Data warehouse and business intelligence
Data mining
Google web search
Big Data analysis on the cloud
Structured data
Unstructured data
Big Data
Customer data
Employee data
Competition data
Summary
Notes
3. Creating value from Big Data
Value drivers in commercial organizations
The proforma income statement and balance sheet
Market value and non-financial values
Investments where Big Data can create value
Creating value from additional revenue from existing customers – higher prices
Creating value from customer satisfaction
Creating value from reduced subscriber acquisition costs
Creating value from more effective marketing – acquiring more customers
Creating value from customer retention value
When data itself is the source of value creation
Summary
Notes
4. Big Data techniques and solutions
Big Data analytics
Operational excellence
Smart decision making
Innovation
Data analytics techniques
Statistical analysis
Social network analysis
Semantics
Data visualization
Predictive analysis
Summary
Notes
5. Introducing the model: design and implementation
C-ADAPT model of Big Data value creation
1. C (Challenges and/or goals)
2. A (Areas identification)
3. D (Data discovery)
4. A (Analysis and insights)
5. P (Presentation and visualization)
6.T (Testing the value created, refine and repeat)
C-ADAPT worksheet
C – Challenges and goals
A – Areas related
D – Data discovery
A – Analysis and insights
P – Presentation and visualization
T – Testing the value created, refine and repeat
Summary
Notes
6. Big Data case studies
Ooredoo (formerly Qtel)
Rebranding and message amplification
Domino’s Pizza
Understanding buying behavior
Leading antivirus company
Increasing engagement and driving revenue
Gate Gourmet
Use of data for competitive analysis
Tesco
Knowing customer insights from data
Delta Airlines
Data is helping them find lost baggage
Intel
Saving manufacturing costs with Big Data
TXU Energy
Saving costs by using smart electric meters
OmedaRx
Big Data to improve medication adherence
John Deere
Revolutionizing farming using Big Data
Airbnb
Price recommendations using Big Data
Walmart
Smart searching using semantic analysis
Huffington Post
Using Big Data to drive the traffic
Summary
Notes
7. What practitioners say
Big Data is important – very important!
Key value from Big Data
Challenges in implementing Big Data projects
Summary
Notes
8. Conclusion and discussion
Index