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DevOps engineers need to do anything: including local server system management, build engineering, release management, cultural promotion, or almost anything related to technology.

10 predictions for the global DevOps market in 2020, and provides action guidelines that technology buyers of the DvOps market need to consider for the technology development route between 2020 and 2025.

In recent years, the ears of DevOps shouting have been seen, but how big is the DevOps market? After studying it, I hope that at least there will be at least an order of magnitude concept for everyone.

In 2020, you will clearly see how continuous updates of DevOps change the delivery method and deliver software to an almost unlimited market.

DevSecOps creates a security awareness and shared knowledge base within the organization to enhance security in the software development process.

As one of the most traditional data applications, data warehouse plays an important role in the enterprise. It is very important for data analysis to build and correctly configure data warehouse.

This article introduces the basic knowledge of data warehouse and data mining.

In mature systems, data analysis is based on data warehouse, OLAP and data mining complement each other

Data warehouse is a collection of subject oriented, integrated, nonvolatile and time variant data to support management decision.

Let's talk about the differences between data warehouse and data mining in this article.

Data warehouse and data mining are both different and interrelated. They can be regarded as a collection of business intelligence tools.

Let's talk about the main application of data warehouse and traditional database in this article.

In a sense, data middle platform is a kind of data warehouse, which is to extract data and establish a data warehouse.

Hive is a data warehouse tool based on Hadoop. It can map structured data files into a database table and provide simple SQL query functions.

This article introduces the architecture of Hadoop offline analysis in real projects.

This article is about big data offline analysis Hadoop project.

The biggest feature of Hive is to analyze big data through SQL-like, and avoid writing MapReduce programs to analyze data.

HIVE can help OLAP analysts use simple SQL statements for data analysis without foundation.

The biggest feature of Hive is to analyze big data through SQL-like, and avoid writing MapReduce programs to analyze data, which makes it easier to analyze data.

This article is about Hive offline case understanding and testing.