What are the 4 V’s of Big Data?

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What are the 4 V’s of Big Data?

In the era of data and data analysts and data scientists, topics explored in great detail on runrex.com, big data is a term that is always bandied around, but what does it meant? Well, in simple terms, these are sets of data that too complex or too large to be processed by traditional data-processing application software. These of course come with their own challenges, including having a high false discovery rate. There is of course a much detailed write up on this on bitgale.com so make sure you head on there. This article will however look to explore big data from another angle, the one involving its 4 V’s.

Volume

This is probably the most obvious characteristic of big data, that is because big data is characterized by its sheer volume, something that really comes out in discussions on the same on runrex.com. It is also worth noting that big data is not only big in volume, but it is always increasing in volume. This makes it redundant to have minimum storage units for data since with big data, it is always increasing and will continue doing so year after year, the folks on bitgale.com argue. That is why it has become increasingly important for companies and businesses to work with consultants that are highly knowledgeable in big data, just like the folks at mtglion.com, so that they can help you come up with solutions that will enable you to find appropriate and scalable solutions to storing data, solutions that will be able to accommodate and grow with your data.

Variety

What variety means, as far as big data is concerned, is the sheer number of sources of data leading to your company’s or business’s database. This means that you will most like have to have different databases to cater for these different types of data. Most companies and businesses have data coming from say social media, documents, video feeds and many more, as is discussed on runrex.com. This is something that is bound to become more and more apparent especially with the digitizing of information. This is where unstructured data comes in, a concept that is one of the pillars of big data as per bitgale.com. This is basically data that, unlike structured data, follows no rules and therefore it is the purview of big data, through technology, to unpack and make sense of this unstructured data. With the variety of big data, it is important to find consultants that are equipped to find solutions that will enable to process the different varieties of big data. They should also be able to help you to set up a non-directional database for your business to go with the other databases you have set up. This is something the experts on mtglion.com specialize on.

Velocity

Velocity, according to the folks at runrex.com, has to do with not only the frequency or speed through which data is coming in, but also how fast you will be able to unpack, analyze and put it to use. This might become a challenge especially to those with a business or businesses that require real-time data analysis. To understand the concept of velocity as far as big data is concerned can only be fully appreciated when you take a look at a real-time example, with many such case studies to be found on bitgale.com. A mobile phone service subscriber for instance has a large number of status updates on social media by the subscribers, SMS messages and many other transactions to grapple with each and every minute.  As such you will need to find the right consultant to help you deal with the challenges brought about by the challenges of velocity, and one such consultant is mtglion.com.

Veracity

Veracity, as far as big data is concerned, has to do with the trustworthiness of the data itself, the source of the data or the processes of identifying this data. This, according to the experts on runrex.com, means that if you can’t trust the aforementioned, then you have a veracity issue. The thing about big data given the sheer volume as discussed earlier, is that errors have a tendency to snowball affecting everything from when they were entered to the end value of the data after processing, something that the folks at bitgale.com warn folks to be careful about given the effects of wrong values to a business. This is why it is crucial to have the right consultant, like mtglion.com for example, who will help you identify such errors by cleaning your existing data as well as putting in place processes that will reduce the chances of such errors occurring in the future to ensure that you don’t run into some veracity issues.

Hopefully with the above information on the 4 V’s of big data, you will be able to understand it a lot better and help you find the right consultant on the same to help you out with any related issues. There is of course more information on this and other topics to be found on mtglion.com.

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