{"id":401,"date":"2022-01-31T00:36:42","date_gmt":"2022-01-31T00:36:42","guid":{"rendered":"https:\/\/windowscommunity.fr\/?p=401"},"modified":"2022-01-31T00:37:10","modified_gmt":"2022-01-31T00:37:10","slug":"the-power-of-leveraging-big-data","status":"publish","type":"post","link":"https:\/\/windowscommunity.fr\/fr\/the-power-of-leveraging-big-data\/","title":{"rendered":"The Power Of Leveraging Big Data"},"content":{"rendered":"
The definition of big data is data that is large in variety, volume, and velocity. The three v’s of big data is something we’ll cover in more detail. The evolution of big data analytics gives rise to the ever-growing online retail market that demands the need to process mass amounts of data to improve business functions. And, it typically can’t be processed by traditional computing software. It requires software that can analyse large amounts of data and quantify it into usable data.<\/p>\n\n\n\n
Below, we’ll look at the history of big data, how businesses can use it, and what the future has in store.<\/p>\n\n\n\n
Large data sets are nothing new. Businesses have had the task of divulging mass amounts of data from as early as the 60s when the world of data really kicked off. But it wasn’t until around 2005 when the growth of Facebook and Youtube dominated the online world – causing industry leaders to realise there was a mass amount of data produced by these platforms. <\/p>\n\n\n\n
Around the same time, a company called Hadoop came to life as an open-source framework with the ability to analyse and store big data sets. More open-source companies formed, but it was Hadoop that set precedence for the world of big data that was to come. They made it possible for big data to be easy to store and process – and in the years since, the volume of big data processing increased ten-fold.<\/p>\n\n\n\n