There has been an exp losion in volume, velocity, and variety of data, and the increased interest in scaling up data collection and analysis has created a huge demand for p rofessionals who can understand the infrastructure for handling huge amount of data. This tutorial uses a practical approach to understand the concept s, principles, and techniques of big data technologies and the infrastructu re components used to support large-scale data science and business intelli gence.
\nThe tutorial will look at technologies and archit ectures for parallel and distributed computing, large-scale data warehousin g, and scale-out data analytics platforms. It will review business use case s for big data application development and seek to understand how to apply big data techniques to solve these business challenges.
\nAtten dees will have a hands-on opportunity to develop example big data applicati ons covering cloud technologies/services and analytics libraries using clou d-native, community development platforms, and open-source tools.
\nA ttendees will learn about:
\n\n Types of big data analytics applications\n The evolution of high-performance big data infrastructure to support big da ta analytics\n Techniques for persisting, virtualizing, and accessing large data objects\n How cloud computing lowers the barriers to entry to big data analytics\n Data lakes and data governance\n Developing a sample API-based application to publish data and empowering da ta consumers to access that data\n\n DTSTART:20200323T083000 SUMMARY:AM7: Introduction to Big Data Analytics Infrastructure DTEND:20200323T114459 LOCATION: See Description END:VEVENT END:VCALENDAR