1 thought on “How do Xiaobai learn big data projects?”
Dianne
If there is a programming set, this is the best, it will save a lot of learning time and make it easier to understand. Because the big data environment is relatively complicated, it is not the same as learning programming software. The machine is installed. Just knocking a few lines of code with the teacher, but big data is more troublesome, at least prepare the virtualized cluster environment, and then It is also necessary to install and deploy various accounting structures, so the demand is endurance, and it is necessary to solve the talents. Persistence is persistent, so that you may learn big data. The learning process I introduced is: to do a good foundation and understand. With more practice, you must set up a programming environment by yourself. After continuously studying SPARK, Python, Storm, Cloud Calculation and other related courses, slowly form a common sense system in your own brain, and your understanding of big data will become more and more thorough.
is the first to get started. The common sense of big data includes many skills. I set the settings based on my many years of work experience and the courses I have collected and organized.
The basic advanced foundation is to learn from Java's speech, and then study and statistical study of Linux. Big data includes several parts, one is the collection and processing of data, and the second is the application of big data. The top part of the list rely on distributed, cloud nuclear abacus, and some special conditions for processing. Data processing skill structure composition is spark structure. Solve the problem of big data storage. Together, the processing of linked databases also needs to learn a large amount of data. Exactly the business data of many large commercial systems is still processed by traditional contact databases.
For Xiaobai how to learn big data projects, Ivy Xiaobian will share with you here. If you have a strong interest in big data projects, I hope this article can help you. If you also want to know the skills and materials of more data analysts and big data engineers, you can click on other articles on this site for learning.
If there is a programming set, this is the best, it will save a lot of learning time and make it easier to understand. Because the big data environment is relatively complicated, it is not the same as learning programming software. The machine is installed. Just knocking a few lines of code with the teacher, but big data is more troublesome, at least prepare the virtualized cluster environment, and then It is also necessary to install and deploy various accounting structures, so the demand is endurance, and it is necessary to solve the talents. Persistence is persistent, so that you may learn big data. The learning process I introduced is: to do a good foundation and understand. With more practice, you must set up a programming environment by yourself. After continuously studying SPARK, Python, Storm, Cloud Calculation and other related courses, slowly form a common sense system in your own brain, and your understanding of big data will become more and more thorough.
is the first to get started. The common sense of big data includes many skills. I set the settings based on my many years of work experience and the courses I have collected and organized.
The basic advanced foundation is to learn from Java's speech, and then study and statistical study of Linux. Big data includes several parts, one is the collection and processing of data, and the second is the application of big data. The top part of the list rely on distributed, cloud nuclear abacus, and some special conditions for processing. Data processing skill structure composition is spark structure. Solve the problem of big data storage. Together, the processing of linked databases also needs to learn a large amount of data. Exactly the business data of many large commercial systems is still processed by traditional contact databases.
For Xiaobai how to learn big data projects, Ivy Xiaobian will share with you here. If you have a strong interest in big data projects, I hope this article can help you. If you also want to know the skills and materials of more data analysts and big data engineers, you can click on other articles on this site for learning.