According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. In the simplest form, the tester supplies the inputs from a row in the table and expects the outputs which occur in the same row.
Test automation helps increase development speed while reducing cost and effort. In this article, we will share how to automate testing to help keep a test automation initiative on the right track with key tips for test execution, design and maintenance for large enterprise applications.
Effectively bringing machine learning to production is one of the biggest challenges that data science teams today struggle with. As organizations embark on machine learning initiatives to derive value from their data and become more “AI-driven” or “data-driven”, it’s essential to find a faster and simpler way to productionize machine learning projects so that they can make business impact faster.
Learning additional languages is a common practice in the Netherlands. In primary school, we learn English and secondary school offers French, German, and a host of other options. Learning a new language and speaking it well is tricky.
As a BI Analyst, have you ever encountered a dashboard that wouldn’t refresh because other teams were using it? As a data scientist, have you ever had to wait 6 months before you could access the latest version of Spark? As an application architect, have you ever been asked to wait 12 weeks before you could get hardware to onboard a new application?
The COVID-19 pandemic is forcing every business to see the world differently. From examining business continuity plans, modernizing workforce plans, or building supply chain resiliency, no facet of business has gone untouched. As organizations combat the economic fallout now and in the coming years, agility has never been more important. The key to remaining agile is a better use of data.
The benefits of building a DevOps culture for software companies are clear. DevOps practices integrate once-siloed teams across the software development lifecycle, from Dev to QA to Ops, resulting in both faster innovation and improved product quality. As a result, most software development teams have deployed tools to enable DevOps practices across their workflow.
The introduction of e-commerce stores has made life so easy for the people. It does not make a difference if you are the consumer or a seller. For a seller, it provides the opportunity to express the worth of their brand and product(s). For a consumer, it gives them an all in one platform, where they can shop for multiple categories. With this, the most significant ease for both parties is to opt for e-commerce business is that you can do all this without taking a step out of their house.
Agriculture (Ag) is the oldest and largest industrial vertical in the world, and its importance continues to grow as it becomes more challenging for people to access healthy and fresh food. A recent Agriculture Analytics Market report, released by Markets and Markets, estimates that by 2023, the global agriculture analytics market size will grow from 585 million to 1.2 billion dollars as demands for real-time data analysis and improved operations increase.
