Big Data Analytics on Amazon Web Services (AWS)

Опубликовано 13 марта 2017, 15:56

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Building or expanding your own data center to handle big data workloads is costly, takes a long time, and doesn’t allow your business to move fast enough. The cloud can help with a lot of these problems. Using the cloud to store and process your data can significantly reduce the cost, scalability, and elasticity issues of managing your own data center. But just deciding to move to the cloud isn’t going to solve your big data problems overnight. The problem is, lots of cloud providers offer just a subset of everything you need.

AWS is different. AWS provides the broadest platform for big data analytics in the market today, with deep and rapidly expanding functionality across big data stores, data warehousing, distributed analytics, real-time streaming, machine learning, and business intelligence. These building blocks – along with capabilities to meet the strictest security requirements – allow customers to quickly and easily tackle a wide range of analytics challenges. No other platform provides this level of depth. That’s why leading organizations like GE, J&J, Philips, Nasdaq, Netflix, Airbnb, Pinterest, as well as many others across every industry, are currently using AWS to run their big data analytic workloads.