Everything you ever wanted to know about big data
What is data? If we go by the standard definitions we see or learn in schools, we will say “Data is a raw collection of numbers and texts in a random order making no sense and when properly worked upon, this data is converted into an understandable form known as information”. But the definition is outdated. Not in the sense that it is wrong, but because data today flows not in the form of data, but rather BIG DATA – a relatively new field that is shaping up to be the backbone of almost all fields of computer study today. Click here to know more about data science course
WHAT IS BIG DATA?
The question of what exactly is big data always arises in a novice person’s mind. So let us try and shed some light on their doubts. Big data is nothing but data that is big in size in terms of volume, velocity, and variety. Now, what does this volume, velocity, and variety mean? Let us understand-
1. Volume: The amount of data that is stored at a place such as say a server farm or a cluster should be humongous in nature. For a simple person, a large amount of data would mean no more than 10GB on average. But the reality is – big data deals with more than the said number for a single person only.
2. Velocity: The flow of this huge amount of data should be very fast. It should not take more than seconds to at-least fetch the data. Delivering it to the destination is an issue of network bandwidth.
3. Variety: The data should have a good amount of contrast in it in regards to the type of data that is stored. Say, for example, data of a single person should not just end with the name and a couple more details. Name, address, blood group, occupation, medical histories are some fields that could be available for the data to be called big data.
WHERE IS IT USED?
As long as the question of big data application exists, the answer in the modern world context is – EVERYWHERE. There is no particular field that deals specifically with big data. However, the biggest fields that operate on big data are banking, online shopping sites, healthcare industries, insurance services, etc. For a perfect instance of a real-life working of big data, imagine you are doing some transactions online. The moment you authenticate your transaction, your account is put in a state called “deadlock” wherein unless and until you complete or cancel your transaction, no one from anywhere on the planet will be able to do another transaction, not even the person whose account it is. It can be considered as momentary freezing of the account. You may ask what role Big Data plays over here. The answer is – think of how many people do a transaction at the same moment as you in the world. The process of locking so many accounts at the same time using traditional techniques is impossible.
Nothing in the world resembles perfect. Not even a system as large as big data. It also faces key challenges such as
1. Capturing – Grabbing and capturing the flow of data whilst it moves from one place to another is a hugely challenging task. Very few technologies that also have to be modified are available to do so on a small scale.
2. Storage – A large area and hardware are needed to store and maintain such a huge pool of data.
3. Curation – This means the preparation of data. Making sense and deriving logic to exploit data is another milestone.
4. Search – Obviously, the time taken to search for a piece of data in such a large pile is like finding a needle in a haystack.
If you are looking to, or are interested in forging a career path in big data, you can try an analytics certification course. They have some really experienced faculty members to help you round the clock and develop the requisite skill sets.
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