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.
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.
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.
What is the significance of digital transformation? This is the answer to the question that every enterprise is looking for, and the most common answer is the reinvention of business processes.
Companies tend to make their Big Data projects large in size and scope when implementing them, but the truth is that most Big Data projects usually end up in failure.
Low-latency analytics is a technology that enables processing and analyzing big data in real time or near real time. It is critical in big data processing because it allows organizations to extract insights from data faster.
To ensure that your organization's big data plan is on track, you need to eliminate the following 10 common misconceptions. Let's look at them together.
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.
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
The British science and technology news media V3 recently listed 10 relevant misconceptions about big data applications.