What Are The Three V’s Of Big Data Analytics?
What are the three V’s that define its characteristics? For me they are: visualization, interpretation and interactivity. If we want to measure something we can best do it by visualizing it or, in other words, putting a chart in front of you that visualizes what we are trying to measure. In the same way that if you are reading a book and are trying to understand what it is written on it you will need to interpret it. Interaction is another way of saying understanding.
The most important quality of big data is its ability to aggregate huge amounts of diverse data and process it in order to provide a result rich product. As we all know, in every field there is always a challenger. Small organizations, say operating a small grocery store will not be able to provide the kinds of services that a multinational corporation can offer because it will be too small. It is very easy to differentiate between what is hot and what is not. The right way of working with big data and defining its characteristics is the challenge that faces the IT managers.
Interactivity, as defined by Wikipedia, is “the ability to interact with or manipulate data through the use of computers or other tools”. It is pretty obvious what this means. A computer can interact with a website, with employees, with customers. Big data analytics offers the ability to collect, organize, analyze and act upon this interactivity in a much more comprehensive manner than any previous technologies.
The third I’m of what are the three I’m big data that often define its characteristics is interpretation. Data interpretation involves coming to an understanding of what is actually being measured. Data mining can be used for this purpose and there are also several online tools that allow you to do this. This is why big data analytics is so useful for businesses looking to improve their profitability.
The fourth V is vizualization which refers to “the visual representation of data in some form”. We can use this concept to represent the entire study of big data analytics. Businesses will have to take the necessary steps to ensure that their data sets are easy to understand and representable in a visual format. Interactivity, interpretation and visualization are very important to business analysts and they need to work closely with IT management to make sure they deliver these services effectively.
The fifth V is adaptation. As mentioned above, big data will continue to change and it will require adaptation to keep up with the pace. Businesses will need to adapt their software to best fit their needs, their customers’ needs and the ever-changing landscape of big data analytics itself. Businesses must make sure that they meet all the goals of big data analysis while still being able to move with the times. Adaptation will be key to successful big data management.
The final V is resiliency and redundancy. Resiliency refers to the ability for a system to function even under worst-case conditions. To what are the three v’s, resiliency refers to the ability for a system to function even under extreme conditions. This might include loss of data or a data center collapse. To ensure that these systems function reliably and resiliently, businesses will need to have redundant systems and network connections at all times.
The five characteristics of what are the three I’s that define big data analytics are essential for any enterprise that wants to take advantage of it and ensure that it maximizes its potential. It is important that you work with a data analyst who is familiar with these and understands how they can impact your business. This way, you will be able to ensure that you are using the tools effectively and maximizing on its potential. You might think that there are other things to consider when setting up your big data analytics. However, if you think about the basic characteristics and understand how they relate to your business, you will be able to use it to its fullest effect.