Introduction to Big Data Analytics thumbnail
slide-image
Pause
Mute
Subtitles not available
Playback speed
0.25
0.5
0.75
1
1.25
1.5
1.75
2
Full screen

Introduction to Big Data Analytics

Published on Nov 05, 20135988 Views

Related categories

Chapter list

Introduction to Big Data Analytics00:00
Outline00:54
Big-Data in numbers00:59
Big Data - a growing torrent01:05
In 60 seconds...02:21
How People Spend Their Time Online03:47
World´s Online Population by Region - 104:51
World´s Online Population by Region - 205:19
How People Spend Their Time05:23
Popular Activities on Internet06:14
Top 10 Most Visited Web Properties06:57
Interesting Facts07:42
Highest and Least Growing Trends of the Future08:46
Big-Data Definitions09:41
…so, what is Big-Data?09:53
Characterization of Big Data: volume, velocity, variety (V3)12:27
The extended 3+n Vs of Big Data13:27
Big-Data popularity on the Web (through the eyes of "Google Trends")14:01
…but what can happen with "hypes"15:25
Motivation for Big-Data16:56
Emerging Technologies Hype Cycle 201217:13
Gartner Hype Cycle for Big Data, 201222:27
Why Big-Data?25:42
Enabler: Data storage26:01
Enabler: Computation capacity26:22
Enabler: Data availability27:04
Type of available data28:19
Data available from social networks and mobile devices 29:55
Data available from "Internet of Things"30:43
Big-data value chain31:47
Gains from Big-Data per sector31:47
Predicted lack of talent for Big-Data related technologies31:49
Big Data Market33:11
2012 Worldwide Big Data Revenue by Vendor ($US millions)33:24
Big Data Revenue by Type, 201236:37
Big Data Market Forecast (2011-2017)37:16
Techniques37:45
When Big-Data is really a hard problem?38:09
What matters when dealing with data?44:42
Meaningfulness of Analytic Answers (1/2)47:35
Meaningfulness of Analytic Answers (2/2)48:18
What are "atypical" operators on Big-Data50:43
Analytical operators on Big-Data58:33
…guide to Big-Data algorithms59:07
Tools59:53
Types of tools typically used in Big-Data scenarios01:00:47
Plethora of "Big Data" related tools01:06:00
Distributed infrastructure01:07:45
Distributed processing01:07:49
MapReduce01:07:50
High-performance schema-free databases01:08:57
Data Science01:08:57
Defining Data Science01:09:17
Statistics vs. Data Science01:09:28
Business Intelligence vs. BI01:10:55
Relevant reading01:11:49
Applications01:12:30
…separate slides01:12:34
Final thoughts01:12:37
Literature on Big-Data01:12:40
…to conclude01:13:33