There are not a few friends who are learning big data visualization. Many wise friends choose to take professional big data training to improve their ability quickly.

But some friends are worried about what big data visualization will do.

IT training/specifically, what big data visualization can't do, this topic, to answer your questions.

1: let's talk about what to learn in big data visualization first, so that we can have a rough idea in our hearts.

To be a qualified big data engineer, you need to have a good mathematical foundation, know common machine learning algorithms, have a data mining background and modeling experience; Proficient in JAVA or Python, familiar with the principle and use of Spark, MLlib and other components of Hadoop ecosystem; Familiar with Scala,R,SQL,Shell, familiar with the use of Linux operating system.

2: Apart from the above skills, big data visualization engineers must 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 thought to learn them well.

But don't worry too much. It's not difficult to master this technology, as long as you adopt a scientific learning method.