1. What is Big Data ?
Big data is the term for a collection of data sets so
large and complex that it becomes difficult to process using on-hand database
management tools or traditional data processing applications. The challenges
include capture, curation, storage, search, sharing, transfer, analysis, and
visualization.
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.
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.
When dealing with larger data sets, organizations face difficulties in being able to create, manipulate, and manage big data.
Big data is particularly a problem in business analytics because standard tools and procedures are not designed to search and analyze massive datasets.
As per Gartner : "Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.
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.
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.
When dealing with larger data sets, organizations face difficulties in being able to create, manipulate, and manage big data.
Big data is particularly a problem in business analytics because standard tools and procedures are not designed to search and analyze massive datasets.
As per Gartner : "Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.
Big data spans three dimensions: Volume, Velocity and
Variety.
Volume (amount of data):
Velocity (speed of data in and out):
Variety (range of data types and sources):
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