Big Data

Big Data

1. Definition

   • Big data is a buzzword, or catch-phrase, used to describe a massive volume of both structured and unstructured data that is so large that it's difficult to process using traditional database and software techniques.
   • Structured Data
     • Data that resides in a fixed field within a record or file is called structured data.
     • Example
       • Our normal database in sql
   • Unstructured Data
     • "unstructured data" usually refers to information that doesn't reside in a traditional row-column database
     • Example
       •  Examples of unstructured  include e-mail messages, word processing documents, videos, photos, audio files, presentations, webpages and many other kinds of business documents.

2. Example of big data

   • An example of big data might be petabytes (1,024 terabytes) or exabytes (1,024 petabytes) of data consisting of billions to trillions of records of millions of people -- all from different sources (e.g. Web, sales, customer contact center, social media, mobile data and so on). The data is typically loosely structured data that is often incomplete and inaccessible.

3. The Importance of Big Data

   • It is used to analyze data and to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smarter business decision making

4. Advantages of using big data

   • 1.Cheap, abundant storage. 2.Faster processors. 3.Affordable open source, distributed big data platforms, such as Hadoop. 4.Parallel processing, clustering, MPP, virtualization, large grid environments, high connectivity and high throughputs. 5.Cloud computing and other flexible resource allocation arrangements.

5. Big Data Growth

   • Growth of big data is increasing widely

6. Technologies used in big data

   • Technologies include A/B testing, crowdsourcing, data fusion and integration, genetic algorithms, machine learning, natural language processing, signal processing, simulation, time series analysis and visualization.

7. Description about big data

   • *Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone.  * It defines Big Data as high volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.

8. IBM Big Data

   • According to IBM, 80% of data captured today is unstructured, from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals, to name a few. All of this unstructured data is Big Data.

9. Analyzing Big Data using Hadoop.

   • ->Organizations are discovering that important predictions can be made by sorting through and analyzing Big Data.  ->However, since 80% of this data is "unstructured", it must be formatted (or structured) in a way that makes it suitable for data mining and subsequent analysis.  ->Hadoop is used to solve this problem .It is the platform for structuring Big Data and  make the data useful for analytics purposes.

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