INTRODUCTION
Source
Now, since we are dealing with data coming from distinct sources, data clusters are formed. Data Clusters contains similar as well as dissimilar data within them, and all the big data tools usually work on these data clusters to divide them into groups where similar data exists.
SOURCES FROM WHERE DATA IS FETCHED
There are a number of sources from where data is being received, few of them are:
- We can get them in tabular from, for example from spreadsheets of Excel.
- Google Forms or different types of surveys.
- Customer reviews.
- We can also get the data about customer history and their searches.
- CCTV Cameras.
- From different smart devices, here the concept of Internet of Things comes into play.
THE V'S OF BIG DATA
Volume: As the name itself suggests that there is an enormous amount of data, and similarly organizations have to collect data from different places or sources, social media, and also from many smart devices aka Internet of Things, the amount collected is crucial too as it determines the value of that data. Volume refers to an amount after which the data becomes Big Data, it helps us determine whether the data is worth calling Big Data or not.
Velocity: The term "velocity" itself refers to speed, and in the domain of Big Data, it refers to the speed of data being generated, how quickly is it being generated from different sources and how rapidly it is being processed. In Big Data, the data is being updated constantly, and on a real-time basis, it is changing and evolving as new data comes in from different sources, devices, websites, sensors etc. It needs to be handle quickly so that the new incoming data can be processed.
Variety: I mentioned in the introduction about structured and unstructured data, well when there was no concept of Big Data, only structured data (databases, spreadsheets, etc) was being considered, but in big data analysis, unstructured data (videos, images, PDFs, etc) is also included and thus increases the variety of data in the data systems of an organizations, which leads to different issues which can only be overcome by unique data management tools.
Veracity: Since the amount of data is massive, and it is coming from many different sources, the quality of data being collected and using for analytics matter. The data being fetched from these sources is raw, and if bad or poor quality or inaccurate data is used for analytics, then it can cause different issues and errors which might cause the downfall of the organization.
Value: The data is flying in from many different sources, but is it all used? No, it isn't, as organizations first have to filter out the data which is valuable to them and which will help them make their business strong. The data is then filtered and the valuable data is used for analytics.
IMPORTANCE OF BIG DATA
- The information we get from Big Data analysis, can help us reduce cost in different areas.
- Big Data can help us make intelligent, important and smart decisions.
- While processing data, we can get information about different errors and causes that might lead to failure of a system, and we can deal with them before they occur.
- It helps to improve customer service. New tools and techniques to handle data has helped companies know the patterns of customer responses.
- An important point is that businesses are able to use data coming from different sources or you can say from outside sources, which help them improve their services, their management, etc.
- With the help of Big Data tools, only that data is used in analytics which is useful and valuable to the company.
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Thank you!!! It means so much.
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Good post greet veer
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read first time about Big data. Your post explain it well.
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