Analysis

Articles

Laptop screen showing test data analytics Applying Data Analytics to Test Automation

Testers gather lots of metrics about defect count, test case execution classification, and test velocity—but this information doesn't necessarily answer questions around product quality or how much money test efforts have saved. Testers can better deliver business value by combining test automation with regression analysis, and using visual analytics tools to process the data and see what patterns emerge.

Harsh Vardhan's picture Harsh Vardhan
Computer showing data analysis Rookie Mistakes in Data Analytics

It's easy to make simple mistakes in data analysis. But these little mistakes can result in rework, errors, and—in the worst case—incorrect conclusions that lead you down the wrong path. Making small process changes can help you steer clear of these mistakes and end up having a real impact, both in the amount of time you spend and in your results. Here are some tips for avoiding rookie mistakes in data analytics.

Nels Hoenig's picture Nels Hoenig
Eyeglasses bringing data on a computer screen into focus Finding the Information inside Your Data

Data analysts have to know a lot about diverse business areas so that our reports provide usable information, not just data. We can use this awareness of the value of information to merge different data sets in order to answer new questions, and even help our users make better decisions. But in order to do this, we need to present not just the data, but the information value represented in that data.

Nels Hoenig's picture Nels Hoenig
Woman holding a magnifying glass to her eye Become a Data Detective

Rapid changes in data availability and analysis tools are leading to evolving expectations for the data analyst role. We can do much more than just generate reports; we have the opportunity to not only process data, but convert it into understandable information and use the knowledge revealed by our work to help change happen.

Nels Hoenig's picture Nels Hoenig

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