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Best Practices for Effective Data-driven Test Automation Approach

May 2, 2018

We live in today's rich world where the only importance for a user is data. From user’s behavior on websites and social media interactions to mobile data usage & device interactions across Internet of Things, brands are flooded with data.

Data-driven test automation is one of the processes that can be acquired for the needs where the number of paths that developers and quality assurance teams can take to leverage automation in their operations. Data-driven test automation places test data as the prime factor.

International Data Corporation (IDC) forecasts the next wave of growth in ICT Industry expanding the overall market opportunity to $5.5 trillion by 2020.

• Based on IDC Research, 74% of enterprise architecture professionals strive to be data-driven
• But only that 29% of organizations are great at transforming that data into actions

Data-driven solutions make forecasts about business functions, recommend what to do straightaway and in many cases take action autonomously.

Forbes contributor Brian Ascher mentions, "Trained analysts are not required to query databases. Instead, business users get solutions directly from the software. And, these solutions typically fed them seamlessly into the flow of business activity, often invisibly."

Why to Adopt Data Driven Test Automation?

Data-driven processes can essentially change how evaluation is solicited by providing detailed insights for informed decision-making, thereby profiting the whole industry. Data-driven solutions forecasts about business functions, command what to do next and in many cases take actions spontaneously. Hence, utilizing appropriate data-driven testing helps to achieve test automation effectiveness & ROI.

This sort of data can yield a precise picture of where projects and test cases can grow from their present states. By using data-driven test automation, Quality Engineers can have a uniform flow of business process objectives that will give them a straightaway idea of what areas need to be changed and what is being done effectively from any table source.

Instead of a standard framework where codes and data are part of an individual unit, data-driven tests point out to two elements as distinct items. The data is hosted in external files and is collected by the code when automated testing is executed.   

Industry expert Ville-Veikko Helppi notes that because of the division of test case and data, the number of test scripts needed is decreased, and testers can easily change elements without modifying the integrity of the tests. "Testers can test their app using different data values and parameters without building any intricacy in a test case or test script". Also, he wrote that "the data asset is easy to add, remove and configure and verifies that it doesn't have any connection to test cases."

Why Bulk data in Data-driven approach doesn’t lead to more insights…?

Data-driven approaches to customer engagements, they are no longer that sufficient, because today's leading brands easily acquire an insight-driven approaches that applies data and analytics at every single possibility to distinguish brand and optimize the entire customer experience.

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Let’s have a look at some detailed approaches for better and clear understanding:

1. TRADITIONAL DATA DRIVEN APPROACH

a) Split Optimization

• Segregate business processes
• Customer personalization brings Intelligence
• Limited to a single channel

b) Rear View Future Analytics

• Previously utilized data
• Assemble trend reports
• Limited flexibility & scalability

c) Limited & Archived Data

• Detached Sources
• Volume and variable limits
• Evaluation

2. INSIGHTS DRIVEN APPROACH

a) End to End Optimization

• Customization during entire customer journey
• Continuous and Versatile
• Individual perspective of Customer

b) Real-Time Actionable Analytics

• Rapid Insights
• Actionable Intelligence
• Flexible, precise and adaptable

c) Combined and Unlimited Data

• Single point of gathering, processing, and storage
• Collection of any type of digital data
• Considerate visitor-level behaviors

Benefits we get from Data-driven Test Automation:

a) Scripts can be created even when the development of an application is still going on.

b) Excess & unnecessary duplication of automated testing scripts effectively gets reduced due to the modular type of design & also due to the use of files or records for both input as well as verified data.

c) In case of any change in functionality, we simply need to update the particular "Business Function" script.

d) Information like data inputs or outputs, expected outcomes get stored in the form of suitably managed text records.

e) This allows better error handling, thereby the resulting test scripts are more robust. This is because of the way that when a script is called, the functions return "TRUE" or "FALSE" values, instead of aborting. By carefully created "recovery" program, we can execute our test scripts basically unattended.

More Insights Always Raises Opportunities…

Forrester Research notes that insight-driven businesses bring insights, not just data to every customer obsessed firms that deliberately tackles experiences and know exactly how to use them for greatest advantage across the entire customer lifecycle.

Insight-driven Business Report

Higher Growth

Insight-driven businesses annual growth prediction likely to grow at an average of 30% or more, track to earn $1.8 trillion by 2021

Better Customer View

72% of insights-driven businesses have implemented an individual customer's perspective vs. only 47% of data-driven businesses

Source:

• Forrester’s Q3 Global State of Strategic Planning, Enterprise Architecture, and PMO Online Survey
• Forrester Research "Insights-Driven Businesses See Better Results"; Leganza, G

Conclusion:

Data can be stored in a file, in a database, on a spreadsheet, or on your desktop, and then utilized as expected to test using format specifics for the evaluation of relevant outcomes. To promote business strategic goals and ROI, QA testing circumstances and methods have their primary objectives as the timely release of quality software products. Data-driven testing helps test methods, describes increased capability in identifying bugs, and can effectively ensure product quality with legitimate inputs that further assures thriving deployment.

Based on these best practices, TestingWhiz helps you promote maximum ROI and profit out of your test automation expense with quality output. It will likewise enable you to test progressively, test speedier and enhance the effectiveness of your test automation program.