Systems | Development | Analytics | API | Testing

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Optimize Mobile App Testing for Speed, Scale, and Coverage

Hosted By: Maxwell Newsom, Solution Engineer, Sauce Labs Ashwini Sathe, Senior Group Product Marketing Manager, Sauce Labs Background: As the mobile industry experiences explosive growth, delivering quality mobile apps at speed and maintaining a seamless customer experience has never been more important. In fact, after using Sauce Labs, customers improved release speeds by up to 50% and achieved a 46% uptick in weekly code deployments.

5 Key Data Governance Principles for Effective Data Management

Digitalization has led to more data collection, integral to many industries from healthcare diagnoses to financial transactions. For instance, hospitals use data governance practices to break siloed data and decrease the risk of misdiagnosis or treatment delays. Therefore, managing data to protect its integrity and security leads to high-quality, reliable data that empowers organizations to make informed decisions.

The Future of Shift-Left in Software Development

According to the NIST research, the cost of detecting and fixing software defects exponentially increases over time. Shift left testing highlights the importance of testing early and frequently in the software development lifecycle (SDLC) to ensure that errors are identified and fixed as soon as possible. This method aligns closely with Agile Testing and DevOps Testing philosophies, which emphasize early and continuous integration.

Defining Asynchronous Microservice APIs for Fraud Detection | Designing Event-Driven Microservices

In this video, Wade explores the process of decomposing a monolith into a series of microservices. You'll see how Tributary bank extracts a variety of API methods from an existing monolith. Tributary Bank wants to decompose its monolith into a series of microservices. They are going to start with their Fraud Detection service. However, before they can start, they first have to untangle the existing code. They will need to define a clean API that will allow them to move the functionality to an asynchronous, event-driven microservice.

FI Transformation: T. Rowe Price's & State Street's Automation Journeys

Discover how Appian’s process automation platform has transformed technology procurement and legal departments, all aimed at catalyzing transformation within the organization. Our expert panel will delve into the adoption journey and share invaluable best practices for maximizing value across teams.

Low Code Integration Tooling | WSO2Con USA 2024

We're thrilled to unveil the brand-new Micro Integrator extension for VSCode, crafted to revolutionize the development experience within the WSO2 Micro Integrator ecosystem. Explore the innovative features seamlessly integrated into this extension and discover how it can elevate your Micro Integrator development process. Join us as we delve into the boundless possibilities!

Data Science vs. Data Analytics: Key Differences

Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science and data analytics. While both fields help you extract insights from data, data analytics focuses more on analyzing historical data to guide decisions in the present. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes. These disciplines differ significantly in their methodologies, tools, and outcomes.