Systems | Development | Analytics | API | Testing

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AI in depth: monitoring home appliances from power readings with ML

As the popularity of home automation and the cost of electricity grow around the world, energy conservation has become a higher priority for many consumers. With a number of smart meter devices available for your home, you can now measure and record overall household power draw, and then with the output of a machine learning model, accurately predict individual appliance behavior simply by analyzing meter data.

Automated Machine Learning: is it the Holy Grail?

Machine learning is in the ascendancy. Particularly when it comes to pattern recognition, machine learning is the method of choice. Tangible examples of its applications include fraud detection, image recognition, predictive maintenance, and train delay prediction systems. In day-to-day machine learning (ML) and the quest to deploy the knowledge gained, we typically encounter these three main problems (but not the only ones).

Observability For Your Microservices Using Kong and Kubernetes

In the modern SaaS world, observability is key to running software reliability, managing risks and deriving business value out of the code that you’re shipping. To measure how your service is performing, you record Service Level Indicators (SLIs) or metrics, and alert whenever performance, correctness or availability is affected.

February Features: Improving QA Metrics & Visibility with Rainforest

Getting the insights you need quickly is essential to understanding and improving your QA process. With that in mind, we’re rolling out a few new features and updates to help teams gain insight into the state of software testing for their team quickly and efficiently.

The 2019 Gartner MQ - Qlik Named a Leader 9 years in a Row!

Today’s always a big day in the analytics world – the release of the annual Gartner Magic Quadrant for Analytics and Business Intelligence. Qlik continues its streak of being positioned in the leader’s quadrant, with today marking our ninth consecutive year. That is consistency in vision and execution a customer can trust. So how did we get here?

Merging Database API Calls with DreamFactory Data Mesh

Enterprises often manage data in multiple databases, often hailing from different vendors and even residing in different clouds. Thanks to DreamFactory's data mesh feature, it's possible to configure your REST API to merge data from disparate databases and present this data within a single response.