Next-Generation Big Data

This book is a practical guide with easy-to-follow examples and case studies on how to supplant or augment traditional enterprise data warehouse and business intelligence environments with modern big data platforms and next-generation third-party applications. The book revolves around Apache Kudu, Impala, and Spark as the triumvirate comprising the modern big data warehouse platform for large-scale data processing and analysis. Next-Generation Big Data takes a holistic approach and covers all aspects of the modern enterprise big data environment, treating each as integrated parts the whole ecosystem. It covers not just the native Hadoop technology stack (Apache Kudu, Spark, Impala, HDFS, etc), but also the next-generation third-party tools and applications for real-time and batch data ingestion and processing (StreamSets, NIFI, Talend, Pentaho, Cask), data visualization (Zoomdata, Tableau, Qlik, etc.), data governance and metadata management (Cloudera Navigator, Informatica Metadata Manager, etc.), data wrangling (Datameer, Trifacta, Alytrix, AtScale, etc.), cloud (Cloudera Navigator on AWS and Azure) and data analysis (Data Science Workbench, Jupyter, Zeppelin). It also covers integration with other data platforms (Oracle, SQL Server, MySQL, HBase, Solr, S3). Finally, the book has an extensive and detailed coverage of big data use cases and interesting real-world case studies from AMD, British Telecom, Cerner, Mastercard, and other Cloudera customers. What you'll learn How to deploy Apache Kudu, Impala, and Spark as a cost-effective alternative or "optimization" to enterprise data warehouse environments An understanding of infrastructure optimization such as EDW/data mart/reporting db/archive db replacements, data archiving, data consolidation and ETL offloading to take advantage of millions of dollars in cost savings New Cloudera features such as Data Science Workbench, Cloudera Altus, Cloudera Navigator, and Cloudera Navigator Optimizer Big data "enterprise" topics such as data governance, meta data management, cloud, in-memory computing, use cases, case studies, etc. Who This Book Is For Business intelligence and data warehouse (BI/DW) architects, big data engineers, data analysts, ETL developers, IT project managers, database/big data managers, consultants, etc. who are making the jump to big data. Also, seasoned big data professionals who needs to update their knowledge, IT professionals without or little Hadoop experience , and CIO/CTO, VP of data engineering, IT/big data managers/directors.