There are many application scenarios for big data, and different application scenarios have different requirements for big data technology, so beginners can choose an application scenario that suits them based on their knowledge structure and the industry environment they are in. The industry application of big data has no more than three major scenarios, one of which is the data collection scenario, the second is the data analysis scenario, and the third is the data application scenario, which can be combined with specific scenarios to develop learning plans.

Data collection application scenarios are very many, many industry sectors in the process of carrying out business, need to first complete the data collection task, and the demand for talent in the field of data collection is relatively large, the entire data collection involves a lot of links, including data collection, organizing and storage of three major parts. Relative to data analysis and application links, data collection is still relatively easy to start, beginners can start learning from the crawler, and then gradually expand and go deeper.

Data analysis is one of the core of big data technology, data analysis is also one of the main ways to realize the value of data, so learning big data technology usually must pay attention to data analysis technology. Data analysis currently has two major ways, one is a statistical approach, and the other is a machine learning approach, the learning of these two ways need a process, you can start from the basic knowledge of statistics, to pay attention to the learning of data analysis tools.

Data application is the export of the value of big data, the current data application goal has two major categories, one of which is to the decision makers, and the other is to the use of the intelligent body, the current with big data is gradually becoming an important carrier of the value of the Internet, the data application goal will also increase the value of a carrier of the classification.

Finally, for big data beginners, no matter which learning scenario to choose, it is best to be able to get the guidance of professionals, which has a very direct impact on improving learning efficiency.

About what are the essential methods of data analytics, Qingteng Xiaobian has shared with you here. If you have a strong interest in big data engineering, I hope this article can help you. If you still want to learn more about data analysts, big data engineers tips and materials, you can click on other articles on this site to learn.