Cloudera Educational Services

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. Download full course description 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: March 1-4, 2026 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

This three-day course provides participants with a comprehensive understanding of the Cloudera platform and its integrated services, including Cloudera Data Warehouse, Cloudera Data Engineering, Cloudera Data Flow, and Cloudera AI. Participants will gain hands-on experience in designing, implementing, and optimizing data workflows and analytics solutions within the Cloudera ecosystem. The course emphasizes practical strategies for building scalable, secure, and efficient data-driven solutions tailored to enterprise needs. Key topics include data ingestion and processing, stream management, query optimization, machine learning integration, and managing resource performance in production environments. Download full course description   DATE: February 22-24, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

Overview Apache NiFi 2.0 is revolutionizing data flow automation. This course provides in-depth knowledge of NiFi 2.0's enhanced capabilities, empowering you to build intelligent, efficient, and governed data pipelines for today's most demanding data challenges. You'll explore AI integration, advanced flow management features, and streamlined Python scripting, enabling you to create data solutions that are not only powerful but also adaptable and maintainable. Learn to build more intelligent and efficient NiFi workflows leveraging the new GenAI and Python processors along with the flow governance tools.   What you'll learn During this course, you learn how to:  Integrate Generative AI with Apache NiFi 2.0, including practical use cases.  Understand the key changes in NiFi 2.0 compared to NiFi 1.x, such as deprecated processors and their new replacements.  Clarify the differences between open-source NiFi 2.0 and Cloudera CFM4 with NiFi 2.0, with a focus on Cloudera-specific processors for GenAI.  Perform a migration from NiFi 1.x to NiFi 2.0 and effectively monitor your new NiFi 2.0 instance.  Who Should Take This Course? This course is designed for developers, data engineers, administrators, and others with an interest in learning NiFi's innovative no-code, graphical approach to data ingest. Although programming experience is not required, basic experience with Linux is presumed, and previous exposure to big data concepts and applications is helpful. Prerequisites Participants should have a foundational understanding of data flow concepts and experience with Apache NiFi. Familiarity with Python programming is beneficial but not mandatory.   DATE: February 22, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

This two-day instructor-led training course teaches students the development and operations skills needed to support Cloudera Streaming Analytics, a framework for low-latency processing and analytics powered by Apache Flink and Cloudera's innovative SQL Stream Builder. Through extensive hands-on exercises, students will gain experience deploying and managing a Flink cluster, developing and running Flink applications, and using SQL Stream Builder's continuous SQL to perform analytics on streaming data. DATE: February 15-16, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more

This course introduces Apache Iceberg, a high-performance open table format for organizing petabyte-scale analytic datasets on a file system or object store, available on Cloudera Data Warehouse and Cloudera Data Engineering on both Private and Public Cloud. Combined with Cloudera Data Platform, Iceberg can enable users to build an open data lakehouse architecture for multi-function analytics and to deploy large-scale end-to-end pipelines. This course covers various aspects of Apache Iceberg, such as benefits, architecture, internal operation, read and write operations, and advanced functions, all while drawing comparisons to Hive and building on the students’ existing knowledge and experience. DATE: February 22-25, 2027 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA 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. DATE: February 1-4, 2026 9:00 - 17:00 (CET TIMEZONE) Virtual Classroom, EMEA Read more