analysis

Articles

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
Desktop computer with monitoring software on the screen, photo by Jakob Owens 7 Ways Monitoring Can Help You Be a Better Tester

Monitoring makes your testing work easier, helps you manage certain biases you may have, and lets you learn a lot about the product, users, and even your own processes. Here are seven concrete benefits testers get from monitored data that you can use to convince your team to implement monitoring—as well as realize for yourself.

Lina Zubyte's picture Lina Zubyte
Dashboard on a computer showing test data results, photo by Carlos Muza Reporting Automated Test Results Effectively

The modern iterative software development lifecycle has developers checking in code to version control systems frequently, with continuous integration handling building and running automated tests at an almost equally fast rate. This can generate an enormous amount of test data. Here’s how you can ensure you are reporting results effectively across your team and realizing all the benefits of that information.

Ajeet Dhaliwal's picture Ajeet Dhaliwal
Man in a suit reading the Business section of a newspaper Getting Started with Business Intelligence Testing

There’s a bit of hype in terms such as business intelligence, data analytics, and data mining. In testing terms, though, it means working with scripts and databases, often without traditional GUI interaction. But core testing skills—analysis, synthesis, modeling, observation, and risk assessment—will still help you go far in business intelligence testing.

Albert Gareev's picture Albert Gareev
STARWEST 2018 Troubleshooting and Understanding Modern Systems: Tools Testers Need
Slideshow

Successful agile testers collaborate with programmers as code is written, isolating problems, troubleshooting defects, and debugging code all along the way to getting the product to done. But modern systems are scaling beyond what traditional teams are able to understand using familiar tools. New appreciation for systems and complexity theory, as well as disciplines and tools around emerging areas such as observability and resilience engineering, are offering solutions that allow teams to actively debug their systems and explore properties and patterns they have not defined in advance. Chris will share the basics of the theory of these new ideas, as well as some tools that support this type of work. He'll show how dynamic analysis can be used to isolate and understand puzzling system behavior.

Chris Blain
Geoff Meyer Analytics, Data, and How Testing Is like Baseball: An Interview with Geoff Meyer
Video

In this interview, Geoff Meyer, a test architect in the Dell EMC infrastructure solutions group, explains how test teams can succeed by emulating sports teams in how they collect and interpret data. Geoff explains how analytics can better prepare you for the changing nature of software.

Jennifer Bonine's picture Jennifer Bonine
Daria Mehra Machine Learning and Artisanal Testing: An Interview with Daria Mehra
Video

In this interview, Daria Mehra, the director of quality engineering at Quid, explains how people can use machine learning to better contextualize data, details the complexity of test automation and how to be sure you have enough test coverage, and defines the term “artisanal testing.”

Jennifer Bonine's picture Jennifer Bonine
Kevin McCaffrey Digital Transformation and the Need to Interpret Data: An Interview with Kevin McCaffrey

In this interview, Kevin McCaffrey, the founder and CEO of Tr3Dent, details why digital transformations have become so important in the software industry and why companies need to understand how to utilize the data they’re getting from internet of things devices.

Josiah Renaudin's picture Josiah Renaudin
Testing code Hybrid Verification: Mixing Formal Methods and Testing

The ability to verify contracts either statically or dynamically, coupled with recent advances in proof technology, has opened up a new and promising approach to verification. Critical code can be proved with formal methods, and less critical code can be verified using traditional testing, with a clear separation at the interfaces between the two.

Ben Brosgol's picture Ben Brosgol

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