Today, the ever-changing technology has increased the complexity of many software products. This has made software testing more vital and challenging for the majority of the organizations. For companies performing proper testing, the time holds the key. In addition, the company must prioritize the testing activities. This is only possible through expert testers, advanced tools, and required infrastructure. Another technology that can help identify failures at the earliest is Predictive Analytics. If applied properly, this data driven technology can help make proactive decisions.
Issues related to operations and costs are the factors which concern many testing companies. This can be reduced by following some of the best testing practices in the industry. However, the situation could be different with every new project.
The most common problems among many companies are cost, time, and operational risks. Some of the reasons due to which such problems arise are mentioned below.
- Managing testing of applications with multiple releases.
- Managing the desired infrastructure and multiple testing tools.
- Choosing right tester when you can’t measure productivity.
- Producing reports in a desired view.
- Identifying issues without knowing it’s after effects.
Predictive Analytics
Through this technology, you can predict the current situation and take necessary measure for the future. Predictive Analytics uses three major techniques:
- Predictive model
- Descriptive model
- Decision model
You can use the desired model based on the client’s requirement. Some of the questions that could be answered by Predictive Analytics, which is otherwise not possible using a conventional tool based reports are mentioned below.
- How it is going to affect the testing project?
- How to improve?
- How complex issues could be solved in the best way?
Integrated Approach
In order to fulfill the requirements, multiple testing tools can be used to perform multiple testing activities. Here, silos are used for each testing tool and stores respective data. This approach of incorporating Predictive Analytics in the integration framework with the latest tools and technologies can help in reducing cost, time, and effort.
Some of the advantages of using Predictive Analytics in Software Testing are mentioned below.
- Selecting right tester for a test
- Monitoring the overall project status
- Identifying issues related to different areas of the project
- Identifying the risks at the earliest
- Identifying the delay and the reason for the same
- Monitoring the productivity of the testing team
- Taking right decisions at key points.
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