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The Cloudera Big Data Architecture Workshop (BDAW) is a 2-day learning event that addresses advanced big data application architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data application architecture problems in general, and then applies them to the design of a challenging system.
Throughout the highly interactive workshop, participants apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for participants to learn techniques for architecting big data systems, not only from Cloudera’s experience but also from the experiences of fellow participants.
More specifically, BDAW addresses advanced big data application architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, minimizing the risk of an unsound architecture and technology selection.
To gain the most from the workshop, participants should have a technical background and working knowledge of technologies such as HDFS, Spark, Map-Reduce, Hive/Impala, data formats and relational database management systems. Detailed API level knowledge is not needed, as there will not be any programming activities.
The workshop will be divided into small groups to discuss the problems and develop solutions. Each group will select a spokesperson who will present the group’s findings to the workshop. There will not be any programming labs, but we will have solutions implemented and deployed in the cloud for demos during the workshop.
Workshop Application Use Cases
Application Vertical Slice
Application Data and Processing
Fault Tolerant Distributed Systems
Bruce Martin is a senior instructor at Cloudera, where he teaches courses on data science, Apache Spark, Apache Hadoop, and data analysis. Previously, Bruce was principle architect and director of advanced concepts at SunGard Higher Education, where he developed the software architecture for SunGard’s Course Signals Early Intervention System, which uses machine-learning algorithms to predict the success of students enrolled in university courses. Bruce’s other roles have included senior staff engineer at Sun Microsystems and researcher at Hewlett-Packard Laboratories. Bruce has written many papers on data management and distributed system technologies and frequently presents his work at academic and industrial conferences. Bruce holds patents on distributed object technologies. Bruce holds a PhD and master’s degree in computer science from the University of California at San Diego and a bachelor’s degree in computer science from the University of California, Berkeley.
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