Cargando…
Disruptive Analytics Charting Your Strategy for Next-Generation Business Analytics /
Learn all you need to know about seven key innovations disrupting business analytics today. These innovations-the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics-are radically changing ho...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berkeley, CA :
Apress : Imprint: Apress,
2016.
|
| Edición: | 1st ed. 2016. |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-1-4842-1311-7 | ||
| 003 | DE-He213 | ||
| 005 | 20220124155955.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 160827s2016 xxu| s |||| 0|eng d | ||
| 020 | |a 9781484213117 |9 978-1-4842-1311-7 | ||
| 024 | 7 | |a 10.1007/978-1-4842-1311-7 |2 doi | |
| 050 | 4 | |a HF54.5-.56 | |
| 072 | 7 | |a KJQ |2 bicssc | |
| 072 | 7 | |a COM005030 |2 bisacsh | |
| 072 | 7 | |a KJQ |2 thema | |
| 082 | 0 | 4 | |a 658.4038 |2 23 |
| 100 | 1 | |a Dinsmore, Thomas W. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Disruptive Analytics |h [electronic resource] : |b Charting Your Strategy for Next-Generation Business Analytics / |c by Thomas W. Dinsmore. |
| 250 | |a 1st ed. 2016. | ||
| 264 | 1 | |a Berkeley, CA : |b Apress : |b Imprint: Apress, |c 2016. | |
| 300 | |a XVII, 262 p. 18 illus., 13 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 505 | 0 | |a Chapter 1: Disruption -- Chapter 2: A Short History of Business Analytics -- Chapter 3: Open Source Analytics -- Chapter 4: The Hadoop Ecosystem -- Chapter 5: In-Memory Analytics -- Chapter 6: Streaming and Real Time -- Chapter 7: Analytics in the Cloud -- Chapter 8: Machine Learning -- Chapter 9: Self-Service Analytics -- Chapter 10: Handbook for Managers. . | |
| 520 | |a Learn all you need to know about seven key innovations disrupting business analytics today. These innovations-the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics-are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. 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. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants. | ||
| 650 | 0 | |a Business information services. | |
| 650 | 0 | |a Business. | |
| 650 | 0 | |a Management science. | |
| 650 | 0 | |a Knowledge management. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Information storage and retrieval systems. | |
| 650 | 0 | |a Computer simulation. | |
| 650 | 1 | 4 | |a Business Information Systems. |
| 650 | 2 | 4 | |a Business and Management. |
| 650 | 2 | 4 | |a Knowledge Management. |
| 650 | 2 | 4 | |a Data Mining and Knowledge Discovery. |
| 650 | 2 | 4 | |a Information Storage and Retrieval. |
| 650 | 2 | 4 | |a Computer Modelling. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781484213124 |
| 776 | 0 | 8 | |i Printed edition: |z 9781484213131 |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-1-4842-1311-7 |z Texto Completo |
| 912 | |a ZDB-2-BUM | ||
| 912 | |a ZDB-2-SXBM | ||
| 950 | |a Business and Management (SpringerNature-41169) | ||
| 950 | |a Business and Management (R0) (SpringerNature-43719) | ||