Whether you know it or not every individual who uses any technology generates mind boggling amount of data every day. Do you know how much of data is piling up on the server? Exabyte’s. This information comes from smart phones, websites, and use of social networking which is appropriately known as “Big Data”. Big Data is revolutionized in various sectors like finance, commerce, medicine, science and in everyday life.
Simply we can define Big Data as large volume of data which is difficult to process by using traditional systems .Big Data is a relative term which depends on the capabilities of the system.
Let’s say you have 100MB of document to share with friend through email or 100GB size of image you want to view on your monitor in real time. These are difficult to process by using traditional system which becomes a Big Data for you. At higher level the term is relative to the organization capabilities.
Even traditional systems like relational databases are not capable of handling Big Data and challenges spring up in multiple levels including storage, capture, search, sharing, analyzing and virtualization. Big Data challenges traditional system not merely because of growing size of files .Big Data also depend how fast the data is coming and various file formats.Measure of Big Data depends on three attributes
Volume – Facebook generates 500TB of new data daily. Every time you share a link, comment on post, click a notification, visit a page, or upload a photo you are generating data for the company to track. Air bus generates 640 TB of data in a one flight, twitter generates 12 TB of data. In past, large amount of data was a storage issue. Today Big data is analyzed to create a value for commercialization
Velocity – The speed of information generated is called “velocity”. Example, in science experiment like atomic reactor where collision of sub atomic particles is recorded ,it generates 40TB of data per second , number of tweets coming in a second, number of Facebook posts coming per second .major challenging task for most organization’s is reacting quickly to tackle the excessive data coming at high frequency .
Variety – Now a day’s data comes in all types of formats. Traditional databases are designed for well-structured data.Today Data also comes in audio, video, text message which are unstructured data .Twitter tweets and social media posts are good examples of unstructured. Many organizations still struggle in managing and manipulating with the different varieties of data
Why Big Data is important?
“More data my lead more accurate results”
There was always large amount of data and computer is all about processing the data .out of the excessive data stored 90% is unstructured and rest is structured .Decision making was solely depended on the 10% structured data. Suddenly organizations/peoples realized there is a hidden value/opportunity to this unstructured Data which they could analyze and create a value out of it for commercial and societal purpose.
Big Data analytics has interesting findings in various sectors like scientific research, logistics, agriculture, healthcare and business operations. For example, agriculture productivity can be increased by knowing the weather, soil and topography.
Organizations using Big Data analytical tools has more lead over other organizations. Big Data analytics has great potential in data–driven marketing which improves their sales, production process efficient and cost–effective.
Driven motive for any organization to work on Big Data analytics is “How to move from Volume to Value?” Organizations grow fast with Big Data you grow faster
Data generation points?
Mobile devices, machine sensors cameras, social Medias, science facilities, micro phones, software’s etc., are various data points through which Big Data is generated
For more Information about Big Data please attend the Code Instruct workshops