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.

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).

The 2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms report is out. And I am sure that the Marketing departments of many analytics vendors are in a frenzy of activity to get their story out with as much spin as possible.

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?

Sabre Airline Solutions (Sabre) supplies applications to airlines that enable them to manage a variety of planning tasks and strategic operations, including crew schedules, flight paths, and weight and balance for aircraft.