According to all kinds of data collected by big data analysis platform, adaptive interfaces are developed respectively. For the existing information system, develop corresponding interface modules to connect with various information systems. The system that can't realize data * * * interface collects data through ETL tools, supports various types of databases, cleans and converts data according to corresponding specifications, and realizes unified storage management of data.

Data preprocessing

In order to make the big data analysis platform more convenient to process data and make the data storage mechanism more scalable and fault-tolerant, it is necessary to combine the data according to the corresponding relevance, convert the data into text format and store it as a file.

Data storage

In addition to HDFS, which has been widely used in data storage in Hadoop, Hbase, a distributed and column-oriented open source database, is also commonly used. HBase is a key/value system deployed on HDFS. Like Hadoop, HBase's goal is to increase computing and storage capacity by continuously adding cheap commercial servers by relying on horizontal expansion.

What are the basic steps of big data collection and storage? Ivy Bian Xiao will share with you here. If you are interested in big data engineering, I hope this article can help you. If you want to know more about the skills and information of data analysts and big data engineers, you can click on other articles on this site to learn.