An overview of common low-hanging fruits to help you get started with machine learning.

I am excited to share that Tricentis has acquired Waldo, a mobile test automation platform. Waldo complements and extends our existing Tricentis mobile testing offerings with new test automation capabilities that will allow our customers to deliver higher quality mobile applications.

A few weeks ago, I wrote a post summarizing "Seven Data Integration and Quality Scenarios for Qlik | Talend," but ever since, folks have asked if I could explain a little deeper. I'm always happy to oblige my reader (you know who you are), so let's start with the first scenario: Database-to-database synchronization.

Application Programming Interface, or API, development is a critical aspect of modern software engineering, enabling diverse software systems to interact and share data seamlessly. The API serves as a contract between different software applications, outlining how they can communicate with one another. Two of the most popular architectural styles for building Web APIs are Representational State Transfer (REST) and GraphQL.

According to Harvard Business Review – Only 3% of Companies’ Data Meets Basic Quality Standards. In the world of data integration, Extract, Transform, and Load (ETL) processes play a vital role in seamlessly moving and transforming data from diverse sources to target systems. However, ensuring the quality and integrity of this data is crucial for accurate decision-making and business success. ETL testing is the key to achieving reliable data pipelines.

The success of businesses like Zoom, DropBox, and Slack demonstrates the power of product-led growth (PLG) as a strategy for scaling software companies in 2023. Central to this approach is event analytics, the practice of analyzing event data from a software product to unlock data-driven insights. Companies following a PLG strategy (“PLG companies”) use this data to inform product development decisions to enhance user experiences and drive revenue.

Integrations are everywhere, and data-sharing between systems is more vital than ever. Software applications use application programming interfaces (APIs) to ensure all moving parts work together. A REST API follows specific guidelines that dictate how applications or devices connect and communicate with one another to make integrations simple and scalable.

Delivering high-quality software solutions quickly and effectively is crucial for competitiveness in today's fast-paced digital environment. By removing barriers between the development and operations teams, DevOps has changed the software development process and allowed businesses to deploy products more quickly and collaborate more effectively. However, this speed increase may also provide new difficulties in preserving software quality.

In our data-driven world, the landscape of product analytics is rapidly evolving. With the rise of Artificial Intelligence (AI) and Machine Learning (ML), we're seeing a seismic shift in how businesses approach product development and enhancement. But how does AI and ML fit into product analytics, particularly for non-technical business leaders and marketers? And more importantly, what does this mean for the future? ‍

Mainframes continue to play a pivotal role in today’s digital landscape, specifically in large-scale, mission-critical industries such as banking, insurance, healthcare, and government. Their impressive transaction handling capabilities, robust security mechanisms, and efficient resource management make them the go-to choice for organizations dealing with large volumes of sensitive, complex data.