Cloudera Educational Services

About This Course In this video you will learn how Cloudera enables key hybrid capabilities like application portability, and data replication in order to quickly move workloads and data to the cloud. Let's explore how Cloudera Data Platform (CDP) excels at following hybrid use cases, through data pipeline replication and data pipeline migration exercises to the public cloud. Develop Once and Run Anywhere De-risk Cloud Migration This Course contains demonstrations showing how to add Private Base clusters as Classic Clusters and use CDP replication Manager to migrate HDFS data,Hive tables to the cloud Provider of your choice. This course includes 30 minutes of video content including demonstrations. Audience and Prerequisites This OnDemand course is suitable for CDP Administrators, data administrators, and data operators. Read more

Cloudera Data Platform (CDP) is a fully integrated edge to AI product set. Cloudera Manager is purposely built as the DevOps tooling for building and managing Cloudera Data Platform. This four-day hands-on course presents detailed explanation, comprehensive theory, key skills, and recommended practices for successful platform administration. Upon completion of this course a CDP Administrator will learn the full range of functionality and capability of Cloudera Manager in supporting Cloudera Data Platform. This course provides an in-depth explanation and skills to become highly productive with Cloudera Manager and Cloudera Data Platform. Cloudera Manager is a full featured and mature DevOps tool. It is used to install, configure, operate, troubleshoot, report, and upgrade CDP. Many CDP Administrators only use a fraction of the capabilities built into Cloudera Manager. This course teaches the architecture, deployment, configuration, logging, reporting, REST API, and much more. The course provides references for architecture and recommended practices used by enterprises around the globe Download full course description  What you'll learn This course teaches installation, configuration, operation, management, incident resolution, and troubleshooting of Cloudera Manager. What to expect This course is an entry point for aspiring CDP Administrators and any CDP Administrators not well familiar with the full range of Cloudera Manager capabilities. Students must have a background in Linux and knowledge of SQL. Students must have access to the Internet to reach the classroom environments, which are located on Amazon Web Services.   Read more

This four-day Analyzing with Data Warehouse course will teach you to apply traditional data analytics and business intelligence skills to big data. This course presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages. What you'll learn Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the ecosystem, learning how to: Use Apache Hive and Apache Impala to access data through queries Identify distinctions between Hive and Impala, such as differences in syntax, data formats, and supported features Write and execute queries that use functions, aggregate functions, and subqueries Use joins and unions to combine datasets Create, modify, and delete tables, views, and databases Load data into tables and store query results Select file formats and develop partitioning schemes for better performance Use analytic and windowing functions to gain insight into their data Store and query complex or nested data structures Process and analyze semi-structured and unstructured data Optimize and extend the capabilities of Hive and Impala Determine whether Hive, Impala, an RDBMS, or a mix of these is the best choice for a given task Utilize the benefits of CDP Public Cloud Data Warehouse What to expect This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Some knowledge of SQL is assumed, as is basic Linux command-line familiarity.   [DATE: Month START - END, YEAR] Virtual Classroom, [APAC, EMEA, AMER] 9:00 - 17:00 (TIMEZONE) Read more

This four-day Analyzing with Data Warehouse course will teach you to apply traditional data analytics and business intelligence skills to big data. This course presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages. What you'll learn Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the ecosystem, learning how to: Use Apache Hive and Apache Impala to access data through queries Identify distinctions between Hive and Impala, such as differences in syntax, data formats, and supported features Write and execute queries that use functions, aggregate functions, and subqueries Use joins and unions to combine datasets Create, modify, and delete tables, views, and databases Load data into tables and store query results Select file formats and develop partitioning schemes for better performance Use analytic and windowing functions to gain insight into their data Store and query complex or nested data structures Process and analyze semi-structured and unstructured data Optimize and extend the capabilities of Hive and Impala Determine whether Hive, Impala, an RDBMS, or a mix of these is the best choice for a given task Utilize the benefits of CDP Public Cloud Data Warehouse What to expect This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Some knowledge of SQL is assumed, as is basic Linux command-line familiarity.   [DATE: Month START - END, YEAR] Virtual Classroom, [APAC, EMEA, AMER] 9:00 - 17:00 (TIMEZONE) Read more

This four-day Analyzing with Data Warehouse course will teach you to apply traditional data analytics and business intelligence skills to big data. This course presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages. What you'll learn Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the ecosystem, learning how to: Use Apache Hive and Apache Impala to access data through queries Identify distinctions between Hive and Impala, such as differences in syntax, data formats, and supported features Write and execute queries that use functions, aggregate functions, and subqueries Use joins and unions to combine datasets Create, modify, and delete tables, views, and databases Load data into tables and store query results Select file formats and develop partitioning schemes for better performance Use analytic and windowing functions to gain insight into their data Store and query complex or nested data structures Process and analyze semi-structured and unstructured data Optimize and extend the capabilities of Hive and Impala Determine whether Hive, Impala, an RDBMS, or a mix of these is the best choice for a given task Utilize the benefits of CDP Public Cloud Data Warehouse What to expect This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Some knowledge of SQL is assumed, as is basic Linux command-line familiarity.   [DATE: Month START - END, YEAR] Virtual Classroom, [APAC, EMEA, AMER] 9:00 - 17:00 (TIMEZONE) Read more

This four-day instructor-led course begins by introducing Apache Kafka, explaining its key concepts and architecture, and discussing several common use cases. Building on this foundation, you will learn how to plan a Kafka deployment, and then gain hands-on experience by installing and configuring your own cloud-based, multi-node cluster running Kafka on the Cloudera Data Platform (CDP). You will then use this cluster during more than 20 hands-on exercises that follow, covering a range of essential skills, starting with how to create Kafka topics, producers, and consumers, then continuing through progressively more challenging aspects of Kafka operations and development, such as those related to scalability, reliability, and performance problems. Throughout the course, you will learn and use Cloudera’s recommended tools for working with Kafka, including Cloudera Manager, Schema Registry, Streams Messaging Manager, and Cruise Control. Month DD - DD, Year Virtual Classroom, AMER/APAC/EMEA 0:00 - 0:00 (Timezone) Read more