Automation for Big Data with DevOps

The respondents rate the importance of automation for new technologies and trends highest for big data, followed by digitalization, cloud, DevOps and Industry 4.0. However, the assessment differs from sector to sector:

While financial service providers focus on big data, automation is critical to the success of Industry 4.0 and digitalization in the retail and industrial sectors. In connection with DevOps, the assessments are identical.

"In the course of digitalization, more and more data is being processed electronically. Automation is needed to cope with the larger volume of data"

comments Stefan Zeitzen, Senior Vice President Sales EMEA at Automic.

"At the same time, this also offers the opportunity to complete processes faster and reduce the risk of errors caused by manual processing. The situation is similar with Industry 4.0, but much more data is generated. The volume of communication also increases."

Automation is obviously so important for big data because, on the one hand, many different data sources have to be analyzed, which are often insufficiently integrated. On the other hand, big data needs to be analyzed as quickly as possible in order to be able to work with the results promptly.

The more frequently manual intervention is required in this process, the longer the analysis takes. With an average rating of 1.8 on a scale of 1 (very important) to 5 (not important at all), financial service providers as well as industry and commerce rate the influence of automation on DevOps as high.

This confirms the trend towards automating the release process in order to put new software into operation faster, more securely and well documented. Shorter innovation cycles enable companies to adapt their processes promptly to new market requirements or offer new services.