There is a saying that goes, 'You can't manage what you can't measure.' In software development, the true measure of effectiveness doesn't lie solely in the lines of code written or the frequency of commits; it's found in the rate at which you deliver tangible value to your users. The ability to consistently provide value to users, promptly respond to their needs, and transform these into functional features is the ultimate gauge of success. In essence, it's not about how frequently you change the code; it's about how often you can positively impact and delight your users with meaningful updates and enhancements.
Common Test Data Challenges
The quest for fast, dependable test data poses numerous hurdles for application development teams, ranging from the speed and quality of data movement to concerns about security and costs throughout the software development lifecycle (SDLC). Below, we outline the most prevalent challenges organizations encounter in managing test data.
Optimise DevOps collaboration through real-time messaging and analytics
With application environments becoming more complex, integrating a robust messaging platform into your QA and DevOps lifecycle, will accelerate software development, testing, delivery and operations. It offers teams the opportunity to get real-time decisions on every stage, from development to release, based on live comparison and insights. This way collaboration regarding the overall project plan and the overall project efficiency is getting improved and the integration testing phase of your projects is simplified and de-risked with less effort.
Faster and Smarter decisions with Validata Sense.ai Analytics
With Validata Sense.ai we have extended our Analytics functionality so clients are now able to centrally analyse and monitor their testing efforts and progress leveraging AI and machine learning.
Why choose Validata Quality Suite over Selenium
It is a fact that test automation shortens development cycles, avoids cumbersome repetitive tasks and create repeatable, reusable test scenarios that can be executed as often as needed to improve software quality. The first step is to identify the right test automation tool that fits your overall requirements from a variety of options available in the market, both commercial and open source.
How to manage complex hierarchical data when working with SWIFT
SWIFT operates a messaging service for financial messages, such as letters of credit, payments, and securities transactions, between member banks and financial services institutions worldwide. Although such formats have proven to be extremely efficient for electronic data exchange, they are typically difficult for humans to understand, manipulate, and validate.
When testing end-to-end transactions that leverage such message formats, sending a single inbound transaction and validating the result can be both difficult and error-prone, and involves complex test suites that leverage large data sets and perform multilayer validation on the outbound transactions.
When testing end-to-end transactions that leverage such message formats, sending a single inbound transaction and validating the result can be both difficult and error-prone, and involves complex test suites that leverage large data sets and perform multilayer validation on the outbound transactions.
AI, Analytics and Test Management, All in One!
Getting Quality Performance right is key to the success of every area of the QA business. Organisations need to see results across projects, departments and geographies in order to make faster and more informed decisions.
How can Business Intelligence and Advanced Analytics deliver benefits to QA and DevOps
The QA and DevOps business is growing increasingly complex over time—due to legacy systems and the evolution into heterogeneous environments such as, software-as-a-service technologies, private clouds, public clouds, mobility, and the numerous integration points in between that keep it all working.
The Top 5 reasons to migrate from HP QC to Validata 360°
The ALM tools from the major software providers like HP QC, are designed to work with traditional structured or waterfall approaches, lacking clear focus on Test Analytics and not being able to support Agile practices and Continuous Delivery.