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
Big Data
Big data has always been a relatively mysterious industry, in recent years because of big data discriminatory pricing only by more than the average person to understand, so have you ever thought about big data whether it is developed or analyzed, where the data inside are coming from?
Human beings and objects are the two major categories of the earth. Human beings are the most advanced animals on the earth. Objects (animals, plants, organisms, microorganisms, man-made objects) cannot be made. Human beings have wisdom and dominate the earth;
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.
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.
The data grid can overcome many challenges inherent in big data by driving higher levels of autonomy and data engineering alliances among a wider range of stakeholders. However, big data is not a panacea, it brings a series of risks for enterprises to manage.
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.
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.
With the gradual development of big data, there is more and more data, and data analysis is especially important.
What we can predict is that the future of big data technology will continue to evolve along the direction of heterogeneous computing, cloudization, AI convergence, and in-memory computing.