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.
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.
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.
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.
Streaming data includes a variety of data, such as log files generated by customers using your mobile or web applications, online shopping data, in-game player activity, social networking site information, financial trading floors, or geospatial services, as well as telemetry data from connected devices or instruments in your data center.
In learning Big Data process, Hadoop is important as a core module for Big Data development.
With the increasing maturity of data analytics technology, research institutes should actively utilize data analytics tools to improve research efficiency.
With the continuous improvement of big data infrastructure, data analytics and business intelligence tools will gradually become the mainstay of big data. Therefore, the big data industry will develop toward these trends in the coming years.
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.
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.