| Interested in Mastering the Hottest New Technologies in Data Management and Analysis? This year, the Data Summit workshops are taking a deep dive into the many benefits of Hadoop and Spark. Whether you're installing and configuring Hadoop in your environment, learning the fundamentals of data exploration, testing the waters with in-memory analytics on big data sets, or want to learn the basics of machine learning, we've got you covered. Register now to reserve your spot at one of these compelling workshops.
Introduction to Hadoop
Hadoop has forever changed the economics and the dynamics of large-scale computing, and its use among enterprises looking to augment their traditional data warehouses continues to grow. Join this workshop to explore the basics of Hadoop, including the Hadoop Distributed File System, MapReduce, and the budding ecosystem of Hadoop software projects. Learn best practices for installing and configuring Hadoop in your environment, managing its performance, and developing Big Data applications.
Introduction to Data Science with Hadoop
Data science, the ability to sift through massive amounts of data to discover hidden patterns and predict future trends, may be the "sexiest" job of the 21st century, but it requires an understanding of many different elements of data analysis. This workshop will dive into the fundamentals of data exploration, mining and preparation using Hadoop, as well as applying the principles of statistical modeling and data visualization in real-world applications.
Introduction to Spark
Built for large-scale data processing, Spark is on the rise as one of the most active open source projects in the marketplace today. By enabling organizations to perform in-memory analytics on big data sets, it offers substantial performance benefits, as well as versatility as a multi-use platform for data scientists. This workshop will provide an overview of its key features, ecosystem, architecture, as well as how to run Spark, connect data sources and start building applications.
Introduction to Machine-Learning with Spark
From recommender systems to disease diagnosis, machine learning is revolutionizing the process of complex decision-making by enabling the analysis of bigger, more complex data sets and the delivery of faster, more accurate results. Spark offers a number of advantages that make it ideal for large-scale machine learning, including a library of machine-learning algorithms for large data. This workshop will dive into the statistical and algorithmic principles for developing scalable real-world machine learning pipelines with Spark.
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