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.
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.
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.
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.
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.
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.
When testing an application, have you ever thought to yourself, "I wonder who uses this"? Examining the app's logs can give you some idea. Logs are helpful for testers because they provide real feedback and insight into an application as it’s being used, as well as information that describes or can even help solve bugs. Here's how to use them to inform your testing.
The hype around the Internet of Things is at its peak. Should you bother learning the skills developers and testers require in this new field, or will it soon become just another trend that's fallen out of favor? Jon Hagar makes a strong case for why the IoT will be relevant even after the clamor dies down, and why its associated skills will serve you well no matter what.
You’ve probably heard the buzz about big data and business intelligence data warehouses. Both deal with collecting information for analysis, but how are they different? When should you use one or the other? This article explains these two data solutions in a user-friendly way with real-world examples.
Before you can achieve continuous delivery, you need to first start implementing continuous integration. Some say CI is just for developers, but testers also play their own important roles. This article describes solutions that will help you add value to the development lifecycle—whether you work in an agile, DevOps, or traditional context.