Cover
Contents
About the author
Acknowledgements
01 Introduction: Why every business is now a data business
The astonishing growth of data, artificial intelligence and the Internet of Things
A brave new (data-driven) world
Are we nearing true artificial intelligence?
The fourth industrial revolution β or Industry 4.0
Other world-changing technologies
Why every business must become a data business
Notes
02 Use cases for data
The six key use cases
Key data use cases in practice
Some industry-specific use cases
How data is revolutionizing the world of business
03 Using data to improve your business decisions
Setting out your key business questions
Understanding and interpreting your data
Curated data dashboards β the fine dining experience
Self-service data exploration dashboards β the raclette grill experience
Raclette grill analytics in the real world
Data democratization and the role of the data translator
Data storytelling
The future of data visualization and storytelling
04 Using data to understand your customers
Understanding customer analytics
Types of customer data
Pioneering the 360-degree customer view
Customer analytics at Netflix
Real-time personalization and micro-moments
Disneyβs Magic Bands
How data enables customer-led design process
The value of personal connections with customers
05 Using data to create more intelligent services
Tech services
New tricks for old dogs
Smart services in banking, finance and insurance
Smart services in healthcare, medicine and pharmaceuticals
Smart services in fashion and clothing
Robots as a service
Smart education and training services
AI itself as a service
Every company is a tech company now
Notes
06 Using data to make more intelligent products
How smart products enable smart services
Autonomous vehicles and mobility
Intelligent home products
Intelligent healthcare products
Intelligent business, industry and manufacturing products
Intelligent sports products
Notes
07 Using data to improve your business processes
Day-to-day processes and the digital twin
Sales, marketing and customer service
Distribution, warehousing and logistics
Product development
Manufacturing and production
Support services β IT, finance and HR
Notes
08 Monetizing your data
Increasing the value of your organization
When data itself is the core business asset
When the value lies in a companyβs ability to work with data
Selling data to customers or interested parties
Understanding the value of user-generated data
Notes
09 Defining your data use cases
Identifying use cases
How does the use case link to a strategic goal?
What is the objective of the use case?
How will you measure the success of the use case?
Who will be the use case owner?
Who will be the data customers?
What data do we need?
What data governance issues need to be addressed?
How do we analyse the data and turn it into insights?
What are the technology requirements?
What skills and capabilities do we need?
What are the issues around implementation we need to be aware of?
Pick the most effective use cases and use them to build a data strategy
Constructing your data strategy
10 Sourcing and collecting data
Understanding the different types of data
Taking a look at newer types of data
Gathering your internal data
Accessing external data
When the data you want doesnβt exist
11 Data governance, ethics and trust
The ethics of AI
Bias and the importance of βcleanβ data
Staying on the right side of the law
Keeping your data safe
Practising data governance
Notes
12 Turning data into insights
The evolution of analytics
Advanced analytics β from science fiction to business fact
Machine learning β the current cutting-edge in AI
Supervised learning
Unsupervised learning
Reinforcement learning
Deep learning and neural networks
Generative adversarial networks (GANs)
Advanced analytics in practice
Types of analytics
No-code and as-a-service AI infrastructure
Notes
13 Creating a technology and data infrastructure
Data, analytics and AI as a service
Collecting data
Storing data
Public, private and hybrid cloud
The importance of avoiding data silos
The future of data storage
Analysing and processing data
Data communication
Data storytelling and visualization
Notes
14 Building data competencies in your organization
The data skills shortage, and what it means for your business
Building internal skills and competencies
Outsourcing your data analytics
Notes
15 Executing and revisiting your data strategy
Putting data strategy into practice
Why data strategies fail
Creating a data culture
Revisiting the data strategy
Notes
16 Looking ahead
The true value of AI
But where will it all end?
How does this relate to what Iβm doing with AI?
Notes
Appendix 1: Data use case template
Appendix 2: Data strategy template
Index