The company provides a cutting-edge predictive maintenance platform that leverages predictive modeling and is optimized through the use of prescriptive algorithms. “The platform allows content management system data to be consumed in real-time to predict the heath of assets employed,” says Quirke. The prescriptive algorithms generate optimized maintenance schedules based on constraints, which maximize asset up-time, usable life, and minimize service costs.
Open source technologies such as Apache Hadoop and Apache Spark act as game changers for big data analytics. Focused at democratizing analytics on big data, Apache Hadoop enables companies to perform high-performance data access, cleansing and analysis on big data. “Leveraging machine learning algorithms in MLLib (Apache Spark) allow data scientists, in conjunction with IT, to build robust advanced analytics applications and deliver analytical insights quickly and efficiently on massive data sets,” says Quirke. Apache Hadoop/Spark enables companies to store and analyze both structured and unstructured data in a far more scalable manner. Combined with scalable text mining capabilities, data scientists are able to extract structured data from unstructured text, and use it to augment predictive models. “The end-result is a far more accurate analysis of information, and this enables better decision making, lower costs, and increased revenues and profits.”
We offer advanced forecasting methodologies to generate more accurate forecasts that include causal variables
QueBIT envisions a world where the Internet of Things (IoT) massively evolves the amount of data for analytics. This will further increase the need for big data strategy and deployment, and both mobility and location awareness will be critical in the maximization of ROI from IoT integrated analytics. “Our go forward strategy is aligned to the ‘Third Platform’ (the convergence of cloud, mobile, social, and analytics), with the IoT being a significant driver for the expansion and adoption of Third Platform,” says Quirke. Furthermore, QueBIT’s growth plans will significantly focus around big data strategy and optimization, traditional data warehousing optimized for analytics, business intelligence, financial and operational modeling, predictive analytics, and decision optimization solutions.