Recorded June 2016
R statistical computing has grown from a research and prototyping tool into a key component of commercial analytics platforms. The greatest evidence of this may be in Microsoft’s acquisition and subsequent embedding of Revolution R in its key data and analytics technologies. Whether used locally or in the cloud, Microsoft R is a powerful tool for data discovery and predictive analytics. And with their commitment to a ‘write once, deploy anywhere’ approach, R code can be written once and deployed in a wide range of data management platforms, enterprise data warehouses, servers, and workstations without re-developing in another production platform.
Watch this session as the BlueGranite advanced analytics team reviews the benefits of R, especially in the Microsoft analytics ecosystem.
Andy is a Principal Consultant at BlueGranite. His passion is helping customers employ modern tools as part of the democratization of data and now data science. Drawing on a diverse background including military service, non-profit work, and over 13 years in enterprise analytics, Andy loves solving complex business problems that require leadership, teamwork, and technical skills. He has expertise in advanced business analytics using R, SAS, Monte Carlo simulation, discrete-event simulation, AzureML, Power BI, and Spotfire.
Senior Solutions Consultant
Mike is a Senior Solutions Consultant at BlueGranite. He's an advanced analytics pro who loves solving data problems, bringing data to life, and working with users to provide actionable insights from data. Mike's concentrations and interests include data visualization and exploration, predictive analytics and machine learning, big data platform, and cloud data platform. He specializes in Microsoft's SQL Server and Power BI, the Azure Data Platform (including Azure Machine Learning, Stream Analytics, etc.), Hadoop (focusing on Pig and Hive), R, and Tableau. His passion is working with clients to design and implement business intelligence and advanced analytics solutions of various sizes and complexity. Check out Mike's blog at www.datamic.net.