Data2Diamonds
De tweede editie van CGI’s populaire Engelstalige boek Data2Diamonds is volledig herzien en uitgebreid. Dit boek geeft waardevolle inzichten in CGI’s activiteiten op het gebied van data en analytics – onze capaciteiten, onze ervaring en onze mensen, waaronder ook onze klanten, met wie we samen ervaringen opdoen en delen. Het boek is onderdeel van onze ‘thought leadership’ reeks, die een leidraad vormt voor informatiemanagement, business intelligence en analytics. Het bedrijfsleven is te complex en dynamisch geworden om enkel op basis van ervaringen uit het verleden en op intuïtie te kunnen managen. Effectief gebruik van de exponentieel groeiende hoeveelheid gegevens is van essentieel belang geworden voor de koplopers in de industrie en de overheid. Dit boek vormt een leidraad voor de wereld van ‘big data analytics’ en legt uit hoe organisaties de kracht van big data kunnen gebruiken om zichzelf te verbeteren en te vernieuwen, doelstellingen te behalen, en concurrenten te overtreffen.
CGI invites you to preview our new Data to Diamonds book. The following pages provide the book’s table of contents and first chapter: Executive Summary-Drivers of Change. For more information on obtaining a full copy of the book, created for our clients and partners, please visit www.cgi.com/d2d-book or email us at data2diamonds@cgi.com
Inhoudsopgave
Introduction
1 Executive summary – Drivers of change
2 Turning data into insights
2.1 Creating value with data and analytics
2.2 Aligning the organization for success
2.3 Managing data as an asset
2.4 Leveraging evolving technologies
2.5 Case study – Maturing analytics in insurance
3 Industry focus
3.1 Financial services
3.2 Healthcare
3.3 Manufacturing, retail and distribution
3.4 Government
3.5 Energy and utilities
3.6 Communications and media
4 The power of customer data
4.1 Fact-based customer interaction
4.2 Case study – Recovering debt
4.3 Customer analytics
4.4 Customer experience
4.5 Case study – Using location intelligence
5 Getting value from device data
5.1 Predictive maintenance
5.2 Case study – Predictive maintenance
5.3 Distribution network analytics
5.4 Case study – Managing renewable energy
5.5 Traffic analytics
5.6 Case study – Optimizing driver behavior
6 Improving performance with analytics
6.1 Optimizing revenue and margin
6.2 Case study – Increasing revenue through pricing
optimization
6.3 Optimizing outcomes within constraints
6.4 Case study – Optimizing resources in healthcare
7 Organizing for analytics excellence
7.1 The skills and capabilities perspective
7.2 The process perspective
7.3 The governance perspective
7.4 The technology perspective
7.5 Case study – Delivering insights as a core business
8 Managing data as an asset
8.1 Organizing data governance
8.2 A value-based implementation approach
8.3 Case studies – Implementing data governance
8.4 Data management functions
8.5 Case study – Improving sales with quality customer data
9 Data and analytics architecture
9.1 Advancing technologies
9.2 Technology blueprint
9.3 Case study – Providing data and analytics as a service
10 Trusted and secure
10.1 Privacy by design
10.2 Case study – Privacy strategy at a major bank
10.3 Securing trusted data
10.4 Analyzing the threats
10.5 Case study – Advanced threat investigation