Big data analytics : a practical guide for managers

By:

Pries, Kim H.; Dunnigan, Robert

Material type: Text

TextPublication details: London CRC Press 2015Description: xix, 556p. 23 cm ; PbkISBN:

978-1482234510

Subject(s):

Big data Data mining Database management

DDC classification:

658.0557 PRI

Online resources:

Click here to access online

Contents:

1. Introduction 2. The mother of invention's triplets : Moore's law, the proliferation of data, and data storage technology 3. Hadoop 4. HBase and other big data databases 5. Machine learning 6. Statistics 7. Google 8. Geographic information systems (GIS) 9. Discovery 10. Data quality 11. Benefits 12. Concerns 13. Epilogue.

Summary: Covering prominent software packages, including Hadoop, Oracle Endeca, and SAP HANA, this book demonstrates the utility and promise of these applications. It also demonstrates the need to understand data quality and the ability of statistics to mislead when due rigor is not applied. As the authors are both ASQ-certified Six Sigma Black Belts, they demonstrate how common statistical tools and investigative methodologies can mitigate risks that arise from limitations in the data.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	H.T. Parekh Library	GSB Collection	658.0557 PRI (Browse shelf(Opens below))	Available		B2265

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Previous	658.0546 SIE Designing quality of service : Solutions for the enterprise	658.054678 REY E-business a management perspective	658.054678 TUR Electronic Commerce 2010	658.0557 PRI Big data analytics : a practical guide for managers	658.0558 HAL Information systems auditing & assurance	658.0563 AGR Prediction machines: the simple economics of artificial intelligence /	658.056312 NET Commercial data mining: processing analysis and modeling predictive analysis projects	Next

SRS/ Rs.4355/-

1. Introduction
2. The mother of invention's triplets :
Moore's law, the proliferation of data, and data storage technology
3. Hadoop
4. HBase and other big data databases
5. Machine learning
6. Statistics
7. Google
8. Geographic information systems (GIS)
9. Discovery
10. Data quality
11. Benefits
12. Concerns
13. Epilogue.

Covering prominent software packages, including Hadoop, Oracle Endeca, and SAP HANA, this book demonstrates the utility and promise of these applications. It also demonstrates the need to understand data quality and the ability of statistics to mislead when due rigor is not applied. As the authors are both ASQ-certified Six Sigma Black Belts, they demonstrate how common statistical tools and investigative methodologies can mitigate risks that arise from limitations in the data.

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