New SwaggerHub DevOps Features Streamline API Workflow in CI/CD Pipelines
SmartBear improves automation and efficiency across software development lifecycle with new SwaggerHub command line interface and Git integration enhancements
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
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Bringing multi-cloud analytics to your data with BigQuery Omni
Today, we are introducing BigQuery Omni, a flexible, multi-cloud analytics solution that lets you cost-effectively access and securely analyze data across Google Cloud, Amazon Web Services (AWS), and Azure (coming soon), without leaving the familiar BigQuery user interface (UI). Using standard SQL and the same BigQuery APIs our customers love, you will be able to break down data silos and gain critical business insights from a single pane of glass.
Building an effective data approach in a hybrid cloud world
“In today’s world of disruption and transformation, there are a few key things that all organizations are trying to figure out: how to remain relevant to their customer base, how to deal with the pressure of disruption in their industry and, undoubtedly, how to look to technology to help deliver a better service.” Paul Mackay Today we are sitting down with Marc Beierschoder, Analytics & Cognitive Offering Lead at Deloitte Germany and Paul Mackay, the EMEA Cloud Lead at Cloudera to dis
Top Benefits of Data-Driven Test Automation
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.
Reach New Speeds and Unlock Unstructured Data Value
Unstructured data is the biggest untapped source of value in your organization, and we can help unlock that value. Since 80% of data is unstructured and growing at an exponential rate, just having BIG data isn’t good enough. You need big data FAST in order to make more accurate and timely decisions. Hitachi Vantara can deliver your data at the speed of business with faster data access to maximize your infrastructure advantage for accuracy, productivity, competitive edge and better outcomes.
How to work with attachments
If you need to work with an attachment – create or send one – there are several connectors that support that. Don’t be confused by what you see now, Simple Trigger is not one of them, but I’m using it here to send some information along the flow. Now what I’m really looking for is the CSV connector, and here I’m using it to create – or, in fact, write a CSV file as an attachment.
How To Get Your DataOps Initiative Prioritized And Paid For
You see the clear and immediate value in DataOps, but your opinion is not the only one that matters. You need your team, your colleagues and your business partners to see that value too – or the project won’t move ahead. In this session, you'll learn the tips and techniques for building an inclusive story. We'll discuss techniques of Design Thinking you can use to translate very technical concepts into business value and outcomes. You will learn practical ways to communicate the value in your DataOps initiative and ensure that it delivers that value when you Implement it.
Serco: Transforming the UK's Prison Services with Low-Code Automation
Serco Plc. is a global company with operations across four regions to support the public sector and other government organizations in citizen services, health, transport, defense, justice and immigration.
Our 6 Favorite Automated Testing Tips
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.
Breaking the Silos Between Data Scientists, Engineers & DevOps with New MLOps Practices
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.