Data is considered the most valuable resource in the modern world since all industrial sectors and business aspects are running based on different kinds of data. Before all of us or machines can use and analyze the data, it is undoubted that data needs to be driven through a set of processing processes, because data is not readable by humans, or unstructured that even machines cannot understand it correctly. Therefore, the effectiveness of industrial and business operations and management also depends on the quality of the data processing steps. That leads to a concern that how we can assure the data processing quality when there are too many different unexpected events such as a larger amount of data than expected comes to the system, or computing resources are suddenly not available anymore. In addition, the development and deployment scripts for processing data can cause hazardous events if engineers make irreversible mistakes. 

—

Cloud computing and DevOps methodology are the rising technologies and terms in recent years. Cloud computing offers fast start-up, flexible, scalable, and elastic computing resources based on the user demand to enhance business operation, while DevOps provides the engineer’s automation features for software development and deployment to reduce human efforts and mistakes. 

As a result, with the help of cloud computing technology and DevOps methodology, the data processing process can be designed and implemented with the most efficient and economic solutions. That leads to the birth of the term DataOps.