Nowadays, there are a few friends who learn big data visualization, and many wise friends choose to participate in professional big data training to quickly improve their ability level. But there are some friends worried about big data visualization will not learn how to do, such a problem. IT training on the specific talk, big data visualization will not learn how to do, this topic, to answer your questions.

1: We first talk about big data visualization to learn what things, so that their hearts have a rough bottom. Want to become a qualified big data engineer, you need to have a good foundation in mathematics, understanding of commonly used machine learning algorithms, data mining background, modeling experience; proficiency in JAVA or Python, familiar with Spark, MLlib and other components of the Hadoop ecosystem principle and use; familiar with Scala, R, SQL, Shell, familiar with Linux Linux.

2: out of the above skills is a big data visualization engineer must master in addition, but also need to master hadoop, hbase, kafka, spark and other distributed data storage and distributed computing platform principles; familiar with big data infrastructure, streaming systems, parallel computing, real-time streaming computation and other technologies have a deep understanding; familiar with SparkStreaming and SparkStreaming. SparkStreaming and SparkSQL, and have a deep understanding of Spark principles and underlying technologies, etc.

3: The depth and breadth of the above skills exist, and it takes some effort to learn them well. However, we do not have to worry a lot, mastering this technology is not difficult, as long as you use the scientific learning method is good.