Wikipedia defines Big Data as a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them and involves use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods to extract value from data, and seldom to a particular size of data.
Didn’t get a single word, right? No issues! This article is meant to crack down this boring definition and provide to you interesting insights into this super amazing thing!
v Big data defined:
There are 4 Vs to understanding big data!
Ø VOLUME: Enterprises like Amazon, Facebook, and Wal-Mart have massive data and more keeps on adding to it on a regular basis. Forbes says we perform 1.2 trillion searches per year.
Ø VELOCITY: This relates to real time sharing of the humongous data base so maintained. It implies the speed at which data is created, shared and analyzed.
Ø VARIETY: Data can be stored in varied forms, ranging from structured data stored in rows and columns to unstructured data to audios to videos and to what not which if analyzed properly at proper times impacts critical decisions.
Ø VERACITY: Data is often unclean and every organization needs to deal with it! When people like you and me submit false information, it leads to piling of junk data.
Who needs this data?
You name a sector and it needs big data analysis. Healthcare? Yes! Government? Yes! Media? Yes! Private Companies? Why not! Information technology? Everyone needs Data
Why would anyone need this data?
All of the above and many more stakeholders use big data to analyze business trends centralize data and for any other critical decisions. Ever wondered why Amazon makes product recommendations to you through their website or e-mail.
It analyzes your past purchases, things you keep in the virtual shopping cart for ages and beyond and all your activity when using their website or app.
What is Hadoop?
It is a free software basically a set of open source programs and procedures that is the backbone of big data operations. It essentially is a tool for big data analytics.
Common misconceptions about Big Data:
Like every second thing, even big data is misunderstood. Organizations confuse big data with Google that will have an answer to all their queries. However, there is a need to tune your expectations from big data. It can help you answer most perplexing and enigmatic query but definitely not everything.
Humongous Career Growth
There are loads and loads of career opportunities in the field of big data analytics. According to a recent Forbes report, about 90% of global organizations report medium to high levels of investment in this area, and about a third call their investments ‘very significant’.
Hadoop skills are in demand! Go tech! Oh, did I forget to mention the pay package? You can earn big.
If you would like to know more about some roles that we are looking to fill in this area, get intouch.
Original article by Deepak Goel