Big Data — What Is Big Data?
What Exactly Is Big Data?
Big Data is a granular form of data that we find in every device connected to the internet. Such data carries a vast variety (which may have anomalies like missing values, or varying values under a respective column), in large volumes (data in PetaBytes and ExaBytes), and with more velocity. Two more v’s have emerged in a few years down the line, which are Value and Veracity. So, now, we have 5 v’s in total for defining Big Data.
5 V’s in Big Data
What these 5 V’s tell us about Big Data, let us understand this:
V1 — Volume (Data Size) — As we discussed, with the advent of Big Data, there comes voluminous data from OTT platforms like Netflix, this low-density, messed up data is directly stored in the disk, which should be of high capacity.
V2 — Velocity (The speed of change) — With billions of users getting added to Fb on daily basis, the alterations in data occur at a high speed that we need some internet-enabled smart products that are real-time and can help us perform real-time evaluation, perform an action on data and gain insights out of it.
V3 — Variety (Variety of Data) — With the advent of large amounts of data on YouTube, we may find audio, and video data types, and in Google, we may find some websites having images only, some videos plus text type, some the combination of three, there can be a list of reviews (a string data type), so we require handling of a variety of data types simultaneously.
Get Palak Grover’s stories in your inbox
Join Medium for free to get updates from this writer.
V4 — Veracity (Uncertainty of Data) — Veracity is the truthfulness of Big Data and the more precise information the data gives, the higher the quality of data and the more reusable the data for analysis.
V5 — Value — With the advent of Big Data, businesses can leverage data and can make precise decisions like cost-cutting, and increasing profits.
How Data is Big Data?
Big Data comes from large sources like OTT platforms, social media platforms like Fb, Twitter, and IoT, YouTube, and much more; however, with big data, the unstructured data increases exponentially.
The volume of data in PB and EB would not be possible with the data processing software we use on daily basis. For instance, to store data and perform analysis on 3 TB of data, you need to have 3 TB of storage, for which you can only refer to supercomputers. Just like we see FB generates around 4 PB of data on daily basis, and handles 40 billion images from its user base and there was a time when it used to take 10 years this much data, now to increase the processing speed (a signal line-of-failure because of a traffic), Google and Fb store their data in their data centers that are distributed globally across various regions; this has helped process the same data within a week.
So, how do these platforms store data, and how big data analysis is done? Well, around 2005, when people realized the importance of Big Data, Hadoop came in handy. Hadoop (more recently Spark, Mapreduce, or BigQuery) are open source frameworks under Apache that have become important in our current lives as they allow us to store Big Data work with and store at a minimal cost.
Conclusion
With Big Data present globally, cheaper and accessible, businessmen can make accurate business decisions.
Therefore, we can say all internet-connected devices have data stored in them and that’s the reason when a new software launches, the developer makes sure that there is no internet connection so as to stop updations and prevent any data from entering the system.
