A renowned airline company employed big data technology to assure a better client experience as part of its goal to provide a pleasant and stress-free flight experience. They wanted to deliver high-quality service that was flexible enough to meet their customers’ changing needs, so the aviation company utilized a connected multi-cloud data platform for enterprise analytics that unified everything—data lakes, data warehouses, analytics, new data sources, and identifying key triggers. They were able to immediately identify pricing and promotion opportunities, reduce and manage churn, and improve web and call center experiences with this solution.

A biotechnology company used big data technology to deepen its understanding of genetic variants, human longevity, and neurological status to develop therapies and treatments for patients around the world. Their previous infrastructure and analytics couldn't handle the massive data sets generated by the rapid expansion of research projects, so they implemented a unified data analytics platform that supported data processing and large-scale statistical analysis. With the use of this technology to enhance scalability and speed, biotechnology companies are now able to deepen their understanding of genetic variants, human longevity, and neurological statuses to develop therapies and treatments for patients around the world.

A circuit manufacturer needed a software to perform fast and efficient quality inspection of printed circuit assemblies right on the conveyor belt in order to detect if any of the PCA components were missing. They employed a desktop application based on image analysis algorithms, complemented with a simple and intuitive GUI. In particular, ORB algorithm was used for feature detection, and a combination of algorithms. This technology provided a fast and reliable solution for Print circuit assemblies (PCA) quality control.

A healthcare service provider needed a system for management and reporting of data on medication inventory, clinical services, patient data, marketing activities and others. They built an analytical Microsoft SQL Server data warehouse, using a Transact-SQL script to load data from the relational database and ensured scalability and short query response time. This allowed them to improve their data management processes.

A retail company introduced image analysis algorithms that automatically captured employee clock in/out times because its equipped CCTV cameras were unable to employ facial identification. The new software solution increased the efficiency of employee monitoring, limited unauthorized activity and reduced the direct involvement of managers in the process.