Concept of Big data

Big data has been a significant reference to data that has been complex and challenging to process using traditional methods. It is referred to as accessing and storing large amounts of information analytics. This has been the case for quite a long time.

However, the concept of big data did gain momentum by the early 2000s. This was when the analyst Doug Laney had modulated the basic definition of big data. He further derived it as an assessment of the three V's.

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●????Volume: This is referred to when organisations do collect data from a lot of many sources, which includes transactions, intelligent devices, types of equipment of industries, images, social media and so on. Previously storing this number of data would have been too costly to maintain., but the advent of technologies like data takes, Hadoop and the cloud did ease the overall burden.

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●????Velocity: With the overall growth in the Internet of Things, specific data streams into businesses at an overwhelming speed had to act promptly. For this, RFID tags, sensors and intelligent meters further drove the need to deal with torrent data in real-time. This gave an overall beginning to the velocity of Big Data.

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●????Variety: This part of the data collection came in various formats, with structured, numeric and traditional data also considered. Furthermore, unstructured text documents also became emails, videos and audio. Overall, various stock ticker data and financial transactions occurred during these times.

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Big data further has profoundly increased the demand for information management specialists. Certain companies like Software AG, Oracle Corporation, IBM, Microsoft, SAP and so on have spent more than $15 billion on software firms specialising in data management and analysis. Starting in 2009, the industry has been worth more than

$100 billion, with more than 10 per cent growth annually. This has been seen within BIG data analytics in recent times.

Big Data is proven effective in a lot of domains. But, while it holds many promises, it will only come with facing challenges. The very first one being it is huge!

Data volumes encompassing the Big Data scenes are engulfed with doubled sizes each year. Several organizations need help to work on things like effectively storing them. Big Data is the next generation, but we know its cons, right?

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