Data is forever. Think about it – it is indeed true. Are you using any application as it is which was built 10 years ago? Are you using any piece of hardware which was built 10 years ago? The answer is most certainly No. However, if I ask you – are you using any data which were captured 50 years ago, the answer is most certainly Yes. For example, look at the history of our nation. I am from India and we have documented history which goes back as over 1000s of year. Well, just look at our birthday data – atleast we are using it till today. Data never gets old and it is going to stay there forever. Â Application which interprets and analysis data got changed but the data remained in its purest format in most cases.
As organizations have grown the data associated with them also grew exponentially and today there are lots of complexity to their data. Most of the big organizations have data in multiple applications and in different formats. The data is also spread out so much that it is hard to categorize with a single algorithm or logic. The mobile revolution which we are experimenting right now has completely changed how we capture the data and build intelligent systems.  Big organizations are indeed facing challenges to keep all the data on a platform which give them a  single consistent view of their data. This unique challenge to make sense of all the data coming in from different sources and deriving the useful actionable information out of is the revolution Big Data world is facing.
Defining Big Data
The 3Vs that define Big Data are Variety, Velocity and Volume.
Volume
We currently see the exponential growth in the data storage as the data is now more than text data. We can find data in the format of videos, musics and large images on our social media channels. It is very common to have Terabytes and Petabytes of the storage system for enterprises. As the database grows the applications and architecture built to support the data needs to be reevaluated quite often. Sometimes the same data is re-evaluated with multiple angles and even though the original data is the same the new found intelligence creates explosion of the data. The big volume indeed represents Big Data.
Velocity
The data growth and social media explosion have changed how we look at the data. There was a time when we used to believe that data of yesterday is recent. The matter of the fact newspapers is still following that logic. However, news channels and radios have changed how fast we receive the news. Today, people reply on social media to update them with the latest happening. On social media sometimes a few seconds old messages (a tweet, status updates etc.) is not something interests users. They often discard old messages and pay attention to recent updates. The data movement is now almost real time and the update window has reduced to fractions of the seconds. This high velocity data represent Big Data.
Variety
Data can be stored in multiple format. For example database, excel, csv, access or for the matter of the fact, it can be stored in a simple text file. Sometimes the data is not even in the traditional format as we assume, it may be in the form of video, SMS, pdf or something we might have not thought about it. It is the need of the organization to arrange it and make it meaningful. It will be easy to do so if we have data in the same format, however it is not the case most of the time. The real world have data in many different formats and that is the challenge we need to overcome with the Big Data. This variety of the data represent  represent Big Data.
Big Data in Simple Words
Big Data is not just about lots of data, it is actually a concept providing an opportunity to find new insight into your existing data as well guidelines to capture and analysis your future data. It makes any business more agile and robust so it can adapt and overcome business challenges.
Tomorrow
In tomorrow’s blog post we will try to answer discuss Evolution of Big Data.
Reference:Â Pinal Dave (https://blog.sqlauthority.com)
19 Comments. Leave new
Nice that others are picking up on Gartner’s 3V’s albeit twelve years after we first introduced and published them in my piece: . The courtesy of a proper citation is always appreciated. –Doug Laney, VP Research, Gartner, @doug_laney
Doug,
You shouldn’t expect a citation for something that is all over the place. I recently read the book by Phil Simon too BIG to IGNORE. He talks about the 3V’s in his book, now he does cite his work but I didn’t read the citations because.. No one cares. I went to your website, while the information was great its a dry looking website. By citing yourself on someone else’s blog just shows everyone how insecure you are about your market share of blog viewers. Respectfully remove your post and twitter handle. No one wants to follow you, sorry pal.
And furthermore, this concept is also published by IBM with no reference to anyone else.. so that is a hard one to try to get rights to.
Yes , it’s only polite to leave a citation. I shall not read the article any further due to the ruseness of the author
Nice piece of info. Thank you!
Thanks Pinal for explanation of big data, earlier I hear about big data but it makes me more clear…thanks once again for your effort for writing on this excellent topic.
Suman
Great topic Pinal .. lookinf frwd to upcoming post !!!
Simple way of writing, Looking forward to see the upcoming topics!!!
This is pretty good explanation with a pretty clear thought, loved your approach and looking forward how you unpack things in another 29 days
Hello Pinal Dave.
We already used a term to describe the transformation from some data in information, called “Business Inteligence”. I understand “big data” could be more than just text information, but is there a specific difference between them ? Until now, look very similar, no ?
great peice of infromation
great piece of infromation
Thanks much for the information.
Hi Dave , You have explained it in very simple and effective manner . The example you are giving are really very easy to understand big data. Thanks
nice article for beginers
nice
thanks Nagasai.
This is a great information to be shared.
Nice article. My own understanding about big data matches with your definition.