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Disruptive analytics : charting your strategy for next-generation business analytics /
Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. --
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[Berkeley, CA]
Apress/Springer Science and Business Media : Apress,
2016.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Dinsmore, Thomas W. | |
| 245 | 1 | 0 | |a Disruptive analytics : |b charting your strategy for next-generation business analytics / |c by Thomas W. Dinsmore. |
| 264 | 1 | |a [Berkeley, CA] |b Apress/Springer Science and Business Media : |b Apress, |c 2016. | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 505 | 0 | |a About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Fundamentals; Disruptive Innovation; The Demand for Data-Driven Insight; Developing a Business Strategy; Managing a Business Unit; Optimizing Business Processes; Developing Products and Services; Differentiating Products and Services; The Analytics Value Chain; Acquiring Data; Data Sources; Data Extraction; Data Cleansing; Data Structuring; Data Consolidation; Managing Data; Delivering Insight; Business Intelligence; Self-Service Discovery; Machine Learning; Overview of the Book. | |
| 505 | 8 | |a Chapter 2: A Short History of AnalyticsBefore the Data Warehouse; Birth of the Relational Database; Early Business Intelligence; Early Statistics and Machine Learning; Disruptive Analytics: Credit Scoring; The Data Warehouse Era; The Enterprise Data Warehouse Movement; Appliances and Columnar Datastores; MOLAP and ROLAP; Statistics, Machine Learning, and Data Mining; Disruptive Analytics: Fraud Detection; Key Trends Today; Digital Transformation of Business; The Data Tsunami; Summary; Chapter 3: Open Source Analytics; Open Source Fundamentals; Definitions; Project Governance. | |
| 505 | 8 | |a Open Source LicensesCode Management and Distribution; Donated Software; The Business of Open Source; Community Open Source; Commercial and Hybrid Open Source; Open Source Analytics; The R Project; Python; Scala; The Disruptive Power of Open Source; Chapter 4: The Hadoop Ecosystem; Hadoop and its Ecosystem; Apache Hadoop; Hadoop 2.0; Powered by Hadoop; Performance Improvements; The Economics of Hadoop; NoSQL Datastores; Analytics in Hadoop; Hadoop 1.0; Apache Hive; Apache Pig; Apache Mahout; Apache Giraph; Datameer; Hadoop 2.0; Apache Spark; Apache Impala; Apache Drill; Presto; Summary. | |
| 505 | 8 | |a Chapter 5: In-Memory AnalyticsIn-Memory Databases; Apache Spark; Capabilities; SQL Processing; Streaming Analytics; Machine Learning; Graph Analytics; Spark in Action; Apache Arrow; Alluxio; Apache Ignite; The New In-Memory Analytics; Chapter 6: Streaming Analytics; A Short History of Streaming Analytics; Fundamentals of Streaming Analytics; Stream Processing; Streaming Operations; Complex Event Processing; Streaming Machine Learning; Anomaly Detection; Streaming Data Sources; Apache ActiveMQ; Apache Kafka; Amazon Kinesis; RabbitMQ; Streaming Analytics Platforms; Apache Apex; Apache Flink. | |
| 505 | 8 | |a Apache SamzaApache Spark Streaming; Apache Storm; Streaming Analytics in Action; Streaming Economics; Chapter 7: Analytics in the Cloud; Cloud Computing Fundamentals; The Business Case for Cloud; Cloud Economics; Data Movement; Security; Analytics in the Public Cloud; Amazon Web Services; Storage Services; Compute Services; Hadoop Services; Database Services; Business Intelligence Services; Machine Learning Services; Marketplace; Microsoft Azure; Storage Services; Compute Services; Hadoop Services; Database Services; Business Intelligence Services; Machine Learning Services. | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. -- |c Edited summary from book. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Business analysts. | |
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| 776 | 0 | 8 | |i Print version: |a Dinsmore, Thomas W. |t Disruptive analytics. |d [Berkeley, CA] Apress/Springer Science and Business Media : Apress, 2016 |z 1484213122 |z 9781484213124 |w (OCoLC)920726800 |
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