The document discusses key aspects of big data including volume, variety, and velocity. It defines big data as large data sets that are difficult to process using traditional software and database management tools. Examples of big data sources mentioned include social networks, medical records, and weather data. Hadoop is presented as a framework for storing and processing big data in a distributed manner. Potential benefits of big data analytics include more accurate data, improved business decisions, increased revenue, and decreased costs.

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5. Volume The amount of Data is big
Variety Different Kinds of data:
Structured
Semi-Structured
Unstructured
Velocity Speed-issues to consider:
How fast is the data available for analysis?
How fast can we do something with it?
Other V’s : Veracity, Variability, Validity, Value, . . .
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How is the Process of
storing the data ??
 before Big Data …
 today’s …
Massively Parallel Processing

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Hadoop is VMware, but the other way around.

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Hadoop as the opposite of a virtual machine

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Example Hadoop distributions

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Use the right tool for the right job!

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•Will be so overwhelmed
•Costs escalate too fast
•Many sources of big data is :
•privacy
•self-regulation
•Legal regulation

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More accurate data
Improved business decisions
Improved marketing strategy and targeting
Increased revenue due to increased customer
decreased costs

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$15 billion on software firms only
specializing in data management and
analytics.
This industry on its own is worth more
than $100 billion and growing at almost
10% a year which is roughly twice as fast
as the software business as a whole.

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In February 2012, the open source analyst
firm Wikibon released the first market
forecast for Big Data , listing $5.1B revenue in
2012 with growth to $53.4B in 2017
The McKinsey Global Institute estimates
that data volume is growing 40% per
year, and will grow 44x between 2009
and 2020.

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Refrences:
[1] senthil sundaresan , BIG DATA ,What, Why,
Where, When and How,
BI/SQL/Data Visualization Evangelist
[2] Koutroumpis, P., & Leiponen, A. 2013.
Understanding the value of (big) data. In
Proceedings of 2013 IEEE international
conference on big data. 38–42. Silicon
Valley, CA, October 6–9, 2013. Los Alamitos,
CA: IEEE Computer Society Press
[3] Gerry George, Martine Haas, Alex “Sandy”
Pentland, FROM THE EDITORS
BIG DATA AND MANAGEMENT, Academy of
Management Journal ,2014, Vol. 57, No. 2,
321–326.
[4] www.Slideshare.com
[5] www.wikipedia.com

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.1Big Data(‫کالن‬‫داده‬)‫را‬‫تعریف‬‫کنید؟‬‫مثال‬‫بزنید‬.‫به‬‫مجموعه‬‫ای‬‫از‬‫داده‬‫ها‬‫گفته‬‫می‬‫ش‬‫ود‬
‫که‬،‫مدیریت‬‫کنترل‬‫و‬‫پردازش‬‫آنها‬‫خارج‬‫از‬‫توانایی‬‫راه‬‫حل‬‫های‬‫نرم‬‫افزاری‬‫موجود‬‫است‬.
‫مانند‬‫شبکه‬‫های‬‫اجتماعی‬،،‫نجوم‬‫مدارک‬‫پزشکی‬،‫داده‬‫های‬‫هواشناسی‬
.2‫سه‬‫تا‬‫از‬‫ویژگیهای‬‫کلیدی‬‫کالن‬‫داده‬‫را‬‫نام‬‫ببرید؟‬‫حجم‬‫داده‬،‫تنوع‬‫داده‬،‫سرعت‬‫ایج‬‫اد‬‫داده‬
.3‫سه‬‫مورد‬‫از‬‫تکنولوژی‬‫ها‬big data‫را‬‫نام‬‫ببرید؟‬pig،hadoop،nosql
.4‫مزیت‬‫های‬big data‫را‬‫بیان‬‫کنید؟‬
o‫داده‬‫های‬‫صحیح‬‫بیشتر‬
o‫توسعه‬‫دادن‬‫تصمیم‬‫های‬‫سازمانی‬
o‫کاهش‬‫هزینه‬‫ها‬
o‫توسعه‬‫دادن‬‫استراتژی‬‫ها‬‫و‬‫اهداف‬‫سازمانی‬
o‫افزایش‬‫درآمد‬‫به‬‫علت‬‫افزایش‬‫مشتری‬

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