====== Big Data For Dummies ======

===== Part 1 : Getting Started with Big Data =====

In this part
  * Trace the evolution of data management
  * Define big data and its technology components
  * Understand the different types of big data
  * Integrate structured and unstructured data.
  * Understand the difference between real-time and non-real-time data
  * Scale your big data operation with distributed computing

==== Chapter 1 : Grasping the Fundamentals of Big Data ====

In this Chapter
  * Looking at a history of data management
  * Understanding why big data matters to business
  * Applying big data to business effectiveness
  * Defining the foundational elements of big data
  * Examining big data's role int the future

==== Chapter 2 : Examining Big Data Types ====

In this Chapter
  * Identifying structured and unstructured data
  * Recognizing real-time and non-real-time requirements for data types
  * Integrating data types into a big data environment

Although data management has been around for a long time, two factors are new in the big data world:
  * Some sources of big data are actually new like the data generated from sensors, smartphone, and tablets
  * Previously produced data hadn't been captured or stored and analyzed in a usable way. the main reason for this is that the technology wasn't there to do so. In other words, we didn't have a cost-effective way to deal with all that data.

=== Defining Structured Data ===
== Exploring sources of big structured data ==

  * **Computer- or machine-generated:** Machine-generated data generally refers to data that is created by a machine without human intervention.
  * **Human-generated:** This is data that humans, in interaction with computers, supply.

== Understanding the role of relational databases in big data ==

=== Defining Unstructured Data ===

== Exploring sources of unstructured data ==

Here are some examples of machine-generated unstructured data:
  * **Satellite images:** This includes weather data or the data that the government captures in its satellite surveillance imagery.
  * **Scientific data:** This includes seismic imagery, atmospheric data, and high energy physics.

The following list shows a few examples of human-generated unstructured data:
  * **Text internal to your company:** Think of all the text within documents, logs, survey results, and e-mails. Enterprise information actually represents a large percent of the text information in the world today.
  * **Social media data:** This data is generated from the social media platforms such as YouTube, Facebook, Twitter, LinkedIn, and Flickr.
  * **Mobile data:** This includes data such as text messages and location information.
  * **Website content:** This comes from any site delivering unstructured content, like YouTube, flickr, or Instagram.

== Understanding the role of a CMS in big data management ==
  * CMS((Content management systems))
  * AIIM((Association for information and Image Management)) : www.aiim.org
  * ECM((Enterprise Content Management))

=== Looking at Real-Time and Non-Real-Time Requirements ===

  * Monitoring for an exception with a new piece of information, like fraud/intelligence
  * Monitoring news feeds and social media to determine events that may impact financial markets, such as a customer reaction to a new product announcement
  * Changing your ad placement during a big sporting event based on real-time Twitter streams
  * Providing a coupon to a customer based on what he bought at the point of sale