Most organizations have developed processes and practices for data management and development of large software projects. While many of these processes and practices are still relevant and valuable, the dramatic growth in volume and variety of data, along with new tools to manage this data, have caused these same organizations to struggle to adapt to this new landscape. This includes understanding how to evaluate new data management systems, how to properly staff projects to ensure success, and how to properly evaluate and manage risks when working with these new management systems.
Jonathan Seidman and Ted Malaska share guidelines and practices to provide a path through the process of developing data projects, from planning to implementation. You’ll leave with insights on managing and delivering your own successful data projects based on Jonathan’s and Ted’s years of experience working with multiple companies and customers.
Jonathan Seidman is a software engineer on the cloud team at Cloudera. Previously, he was a lead engineer on the big data team at Orbitz, helping to build out the Hadoop clusters supporting the data storage and analysis needs of one of the most heavily trafficked sites on the internet. Jonathan is a cofounder of the Chicago Hadoop User Group and the Chicago Big Data Meetup and a frequent speaker on Hadoop and big data at industry conferences such as Hadoop World, Strata, and OSCON. Jonathan is the coauthor of Hadoop Application Architectures from O’Reilly.
Ted Malaska is a director of enterprise architecture at Capital One. Previously, he was the director of engineering in the Global Insight Department at Blizzard; principal solutions architect at Cloudera, helping clients find success with the Hadoop ecosystem; and a lead architect at the Financial Industry Regulatory Authority (FINRA). He has contributed code to Apache Flume, Apache Avro, Apache Yarn, Apache HDFS, Apache Spark, Apache Sqoop, and many more. Ted is a coauthor of Hadoop Application Architectures, a frequent speaker at many conferences, and a frequent blogger on data architectures.
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