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Leaders and innovators : how data-driven organizations are winning with analytics /
"An integrated, strategic approach to higher-value analytics Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows how businesses leverage enterprise analytics to gain strategic insights for profitability and growth. The key factor is integrated, end-to-end capa...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken :
Wiley,
2016.
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| Colección: | Wiley and SAS business series.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Cover; Title Page; Copyright; Contents; Foreword; Acknowledgments; About the Author; Introduction; Chapter 1 The Analytical Data Life Cycle; Stage 1: Data Exploration; Stage 2: Data Preparation; Stage 3: Model Development; Stage 4: Model Deployment; End-to-End Process; Chapter 2 In-Database Processing; Background; Traditional Approach; In-Database Approach; The Need for In-Database Analytics; Success Stories and Use Cases; E-Commerce: Data Preparation and Data Processing; Telecommunication: Developing a Data Model Using In-Database Technology.
- Financial: In-Database Model Development and Deployment; In-Database Data Quality; Background; Data Quality Defined; Business Challenges; Data as a Strategic Asset; The Value of In-Database Data Quality; Data Auditing and Standardization; Data Consolidation and Matching Analysis; Other In-Database Data Quality Functions; Value of In-Database Data Quality; Investment for In-Database Processing; Endnotes; Chapter 3 In-Memory Analytics; Background; Traditional Approach; In-Memory Analytics Approach; The Need for In-Memory Analytics; Benefits; Getting Started; Requirements.
- Success Stories and Use Cases; Global Financial Company: Explore and Analyze Sales and Business Operations; European Government Agency: Analyze Tax and Population Data; Investment for In-Memory Analytics; Chapter 4 Hadoop; Background; Hadoop in the Big Data Environment; Use Cases for Hadoop; Hadoop Fits in the Modern Architecture; Hadoop Architecture; Best Practices; Benefits of Hadoop; Use Cases and Success Stories; Global Online and Social Networking Website; Global Consumer Transaction Company: Data Landing Zone.
- Global Payment Services Company: Hadoop Combining Structured and Semi-Structured Data; A Collection of Use Cases; Endnote; Chapter 5 Bringing It All Together; Background; Collaborative Data Architecture; Staging Warehouse; Fit for Purpose Data Mart; Scenarios for the Collaborative Data Architecture; How In-Database, In-Memory, and Hadoop Are Complementary in a Collaborative Data Architecture; Use Cases and Customer Success Stories; Large U.S. Retailer: In-Database and In-Memory with No Hadoop; International IT Company: In-Memory with Hadoop as an Extension to the Data Warehouse.
- National Railroad Company: In-Database, In-Memory, with Hadoop; Investment and Costs; Endnotes; Chapter 6 Final Thoughts and Conclusion; Five Focus Areas; Cloud Computing; Types of Cloud Computing; Deployment of the Cloud; Benefits of Cloud Computing; Disadvantages of Cloud Computing; Security: Cyber, Data Breach; Security Gaps in the Traditional Approach; Hackers; Automating Prescriptive Analytics: IoT, Events, and Data Streams; Value of Prescriptive Analytics; Leveraging the Internet of Things (IoT); Cognitive Analytics; Evaluating Cognitive Analytics; Expectations and Looking Ahead.