Power Generation companies constantly need predictive analytics to learn about their system (especially with gaining equipment).
Our client required expert eyes to learn about the systems in place and why there is a performance gap. Let’s how we used latest technologies to help them do predictive analytics and found the issues behind performance gap.
Learn how we solved our eCommerce client’s real-time analytics problem in Azure. Our client uses multiple technologies to achieve proper dataflow, including Apache Spark and deep learning technologies. We went ahead and optimized data capture and flow and ensured they got accurate real-time analytics in Azure.
Look at how our AWS experts built a data lake for enterprise clients, providing them with a centralized repository for their data. Once set up, clients can run various analytics, including real-time analytics, helping them to solve decentralized data problems. It also solved slow data analytics and made auditing data across devices and sources easy for the client.