2013 is called the first year of big data, and all walks of life are gradually opening the era of big data applications. Until now, big data is still talked about.
Big Data
Big data has been closely related to our life, many enterprises have started to use big data, even a small thing in our life may be related to big data.
The enterprise data space is growing twice as fast as the consumer data space, in part because organizations are increasingly using the cloud for storage and consumption. Much of this raw data is often located in disparate silos at the point of collection, limiting its use in the enterprise.
When executives hear the term "big data", they naturally think of an amazing amount of available data. This data comes from e-commerce and omni channel marketing, or from connected devices on the Internet of Things, or from applications that generate more detailed information about trading activities.
Data Lake is a term that has emerged in the past decade to describe an important part of the data analysis pipeline in the big data world.
Python as a recognized language suitable for big data, want to do big data development and big data analysis, not only to use Java, Python is also very important a core.
When it comes to big data, many people can say some, but if you ask what are the core technologies of big data, it is estimated that many people will not be able to say
Although big data may seem advanced, but in these years of development, there have been many cases close to our lives, but we may not realize that this is actually "big data" in action.
The British science and technology news media V3 recently listed 10 relevant misconceptions about big data applications.
In the digital age, the emergence of disruptive technologies has changed the nature of lending. Thanks to big data, the lending process is now less about the bank and more about the customer.