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By GigaOM Pro
Table of contents
INTRODUCTION 5
BIG DATA: BEYOND ANALYTICS — BY KRISHNAN SUBRAMANIAN 6
Data quality 7
Data obesity 9
Data markets 11
Cloud platforms and big data 12
Outlook 14
THE ROLE OF M2M IN THE NEXT WAVE OF BIG DATA — BY LAWRENCE M. WALSH
16
The M2M tsunami 18
Carriers driving M2M growth 20
The storage bits, not bytes 22
M2M security considerations 23
The M2M future 25
2012: THE HADOOP INFRASTRUCTURE MARKET BOOMS — BY JO MAITLAND 26
Snapshot: current trends 27
Disruption vectors in the Hadoop platform market 29
Methodology 29
Integration 31
Deployment 32
Access 33
Reliability 34
Data security 36
Total cost of ownership (TCO) 37
Hadoop market outlook 38
Alternatives to Hadoop 39
CONSIDERING INFORMATION-QUALITY DRIVERS FOR BIG DATA ANALYTICS —
BY DAVID LOSHIN 41
Snapshot: traditional data quality and the big data conundrum 42
Information-quality drivers for big data 45
Expectations for information utility 45
Tags, structure and semantics 46
Repurposing and reinterpretation 48
Big data quality dimensions 49
Data sets, data streams and information-quality assessment 50
THE BIG DATA TSUNAMI MEETS THE NEXT GENERATION OF SMART-GRID
COMPANIES — BY ADAM LESSER 52
Meter data management systems (MDMS): going beyond the first wave of smart-grid
big data applications 53
Apply IT to commercial and industrial demand response: GridMobility, SCIenergy,
Enbala Power Networks 54
Using IT to transform consumer behavior 57
Finally, the customer 60
BIG DATA AND THE FUTURE OF HEALTH AND MEDICINE — BY JODY RANCK,
DRPH 62
Calculating the cost of health care 63
Health care’s data deluge 65
Challenges 66
Drivers 67
Key players in the health big data picture 69
Looking ahead 71
WHY SERVICE PROVIDERS MATTER FOR THE FUTURE OF BIG DATA — BY
DERRICK HARRIS 74
Snapshot: What’s happening now? 75
Systems-first firms 75
Algorithm specialists 76
The whole package 77
The vendors themselves 77
Is disruption ahead for data specialists? 78
Analytics-as-a-Service offerings 79
Advanced analytics as COTS software 80
What the future holds 82
CHALLENGES IN DATA PRIVACY — BY CURT A. MONASH, PHD 84
Simplistic privacy doesn’t work 85
What information can be held against you? 87
Translucent modeling 89
If not us, who? 91
ABOUT THE AUTHORS 94
About Derrick Harris 94
About Adam Lesser 94
About David Loshin 94
About Jo Maitland 95
About Curt A. Monash 95
About Jody Ranck 95
About Krishnan Subramanian 96
About Lawrence M. Walsh 96
ABOUT GIGAOM PRO 97 |
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