January 2015
Beginner to intermediate
432 pages
12h 34m
English
book
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data
by EMC Education Services
Content preview from Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data
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Index
Numbers & Symbols
\ (backward slash) as separator, 69
/ (forward slash) as separator, 69
1-itemsets, 147
3 Vs (volume, variety, velocity), 2–3
A
accuracy, 225
ACF (autocorrelation function), 236–237
ACME text analysis example, 259–260
aggregates (SQL)
aggregators of data, 18
AIE (Applied Information Economics), 28
algorithms
CART, 204
ID3, 203
Alphine Miner, 42
alternative hypothesis, 102–103
analytic projects
BI analyst, 362
business users, 361
data engineer, 362
data scientists, 362
DBA (Database Administrator), 362
key points, 372
model description, 371
outputs, 361
presentations, 362
project manager, 362
project sponsor, 361
technical specifications, 376–377
analytic sandboxes. See sandboxes
analytical architecture, 13–15
analytics
business drivers, 11
aov( ) function, 78
Apache Hadoop. See Hadoop
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.