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What’s New in Apache Cassandra 4.0 Apache Cassandra is an open source, distributed NoSQL database based on the wide column model. The highly scalable, highly available database is great for handling large amounts of data. There is no set release date yet for the next version, Cassandra 4.0, but we do already know about several new features. |
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Figuring Out Your Regression Testing Strategy When your application is scheduled to go to production, the development team may be asked what their regression testing strategy is. This is a perfectly reasonable question, but a lot of people have a hard time answering it. Don't overcomplicate it. Analyze your process, look at the other testing, and put it together. |
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Is the Problem with Your Agile Tool, or How You’re Using It? While using index cards and a wall can function just fine as a kanban or Scrum board, issue-tracking tools such as Jira can make it easier to manage a backlog, especially with a distributed team. But these tools are more complex to use and can add their own overhead to the process. You need to keep things simple. |
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Making (and Keeping) Project Risk Visible Project managers recommend how much should be invested to address various risks based on their understanding of project context, but the final decision about what to do and when those efforts are sufficient belongs to the sponsor. Risk management requires executive input, so sponsors need to see all risk data you have. |
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Fueling Innovation through Design Thinking Organizations must embrace new technologies in their product engineering efforts to stay ahead of the curve. But there is another quality that will be key this decade to giving product teams a proactive advantage: design. Design thinking should be embraced not just by designers, but by everyone involved with a product. |
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Machine Learning and Deep Learning: What's the Difference? Many people think that machine learning and deep learning are each just a fancy way to say artificial intelligence, but that is a misconception. Both terms represent subsets of AI technology, but they are different, and their differences dictate the functionality and application of these two software solutions. |
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Pros and Cons of Codeless Test Automation To create automated tests for software applications, testers have historically needed to be able to code in programming languages. Codeless testing eliminates the need for scripting from scratch every time, but in addition to its advantages, there are also some drawbacks. Is codeless automation right for your team? |
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2 Ways to Get Better at Test Automation Many people in testing roles want to grow their skills and learn to build some tests with code. But no matter how well you test, automation is programming work. If you want to get better at automation, your best bet is to get into a role where you are dealing with code. Here are two ways you can break in and learn. |