| Description |
1 online resource (ix, 221 pages) : illustrations (chiefly color) |
| Series |
Wiley and SAS business series |
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Wiley and SAS business series.
|
| Contents |
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 |
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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 |
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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 |
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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 |
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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 |
| Summary |
"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 capabilities that encompass data management and analytics from a business and IT perspective; with analytics running inside a database where the data reside, everyday analytical processes become streamlined and more efficient. This book shows you what analytics is, what it can do, and how you can integrate old and new technologies to get more out of your data. Case studies and examples illustrate real-world scenarios in which an optimized analytics system revolutionized an organization's business. Using in-database and in-memory analytics along with Hadoop, you'll be equipped to improve performance while reducing processing time from days or weeks to hours or minutes. This more strategic approach uncovers the opportunities hidden in your data, and the detailed guidance to optimal data management allows you to break through even the biggest data challenges. With data coming in from every angle in a constant stream, there has never been a greater need for proactive and agile strategies to overcome these struggles in a volatile and competitive economy. This book provides clear guidance and an integrated strategy for organizations seeking greater value from their data and becoming leaders and innovators in the industry. Streamline analytics processes and daily tasks Integrate traditional tools with new and modern technologies Evolve from tactical to strategic behavior Explore new analytics methods and applications The depth and breadth of analytics capabilities, technologies, and potential makes it a bottomless well of insight. But too many organizations falter at implementation--too much, not enough, or the right amount in the wrong way all fail to deliver what an optimized and integrated system could. Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows you how to create the system your organization needs to dramatically improve performance, increase profitability, and drive innovation at all levels for the present and future"-- Provided by publisher |
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"The uniqueness and value of this book is to exploit an integrated, end-to-end capabilities that encompass data management and analytics from a business and IT perspective"-- Provided by publisher |
| Notes |
Includes index |
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Machine generated contents note: Foreword Acknowledgments About the Author(s) Introduction Chapter 1: The Analytical Data Lifecycle Chapter 2: In-Database Processing Chapter 3: In-Memory Analytics Chapter 4: Hadoop Chapter 5: Bringing It All Together Chapter 6: Final Thoughts and Conclusion Afterword Index |
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Online resource; title from digital title page (viewed on June 28, 2018) |
| Subject |
Information visualization.
|
|
Decision making -- Statistical methods
|
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Management -- Statistical methods
|
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BUSINESS & ECONOMICS -- Decision-Making & Problem Solving.
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Decision making -- Statistical methods
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Information visualization
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Management -- Statistical methods
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Data visualisation.
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Prise de décision -- Méthodes statistiques.
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Gestion -- Méthodes statistiques.
|
| Form |
Electronic book
|
| ISBN |
9781119276913 |
|
1119276918 |
|
9781119276920 |
|
1119276926 |
|
9781119449393 |
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1119449391 |
|
