There are not a few friends who are learning big data visualization, and many wise friends choose to participate in professional big data training to quickly improve their abilities. But some friends worry that big data visualization will not do anything. IT training/specifically, big data visualization will not do anything about this topic to answer your question.

1: Let's talk about big data visualization first, so that we can have a general idea. To be a qualified big data engineer, you need to have a good mathematical foundation, understand commonly used machine learning algorithms, and have data mining background and modeling experience; Proficient in JAVA or Python, familiar with the principle and use of Hadoop ecosystem components such as Spark and MLlib; Familiar with Scala, R, SQL, Shell, familiar with the use of Linux operating system.

2. In addition to the above skills, big data visualization engineers must also master the principles of distributed data storage and distributed computing platforms such as hadoop, hbase, kafka and spark. Familiar with big data infrastructure, have a deep understanding of streaming system, parallel computing, real-time streaming computing and other technologies; Familiar with SparkStreaming and SparkSQL, and have a deep understanding of Spark principle and underlying technology.

3. The depth and breadth of the above skills exist, and it takes some thinking to learn them well. But you don't have to worry too much. It is not difficult to master this technology, as long as you adopt scientific learning methods.