Talend Big Data Integration Training Course

This instructor-led, live training in Brazil (online or onsite) is designed for advanced-level data professionals who aim to optimize data processing workflows, ensure data integrity, and implement robust data lakehouse solutions capable of handling the complexities of modern big data applications.

Upon completion of this training, participants will be able to:

• Gain a deep understanding of Iceberg’s architecture, including metadata management and file layout.
• Configure Iceberg for optimal performance across various environments and integrate it with multiple data processing engines.
• Manage large-scale Iceberg tables, execute complex schema changes, and handle partition evolution.
• Master techniques to enhance query performance and data scan efficiency for large datasets.
• Implement mechanisms to ensure data consistency, manage transactional guarantees, and handle failures in distributed environments.

This instructor-led, live training in Brazil (online or onsite) is aimed at beginner-level data professionals who wish to acquire the knowledge and skills necessary to effectively utilize Apache Iceberg for managing large-scale datasets, ensuring data integrity, and optimizing data processing workflows.

By the end of this training, participants will be able to:

• Gain a thorough understanding of Apache Iceberg's architecture, features, and benefits.
• Learn about table formats, partitioning, schema evolution, and time travel capabilities.
• Install and configure Apache Iceberg in different environments.
• Create, manage, and manipulate Iceberg tables.
• Understand the process of migrating data from other table formats to Iceberg.

This instructor-led, live training in Brazil (online or onsite) targets intermediate-level data scientists and engineers who wish to utilize Google Colab and Apache Spark for big data processing and analytics.

By the conclusion of this training, participants will be able to:

• Set up a big data environment using Google Colab and Spark.
• Process and analyze large datasets efficiently with Apache Spark.
• Visualize big data in a collaborative environment.
• Integrate Apache Spark with cloud-based tools.

Apache NiFi is an open-source, flow-based data integration and event-processing platform. It enables automated, real-time data routing, transformation, and system mediation between disparate systems, with a web-based UI and fine-grained control.

This instructor-led, live training (onsite or remote) is aimed at intermediate-level administrators and engineers who wish to deploy, manage, secure, and optimize NiFi dataflows in production environments.

By the end of this training, participants will be able to:

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows from varied sources and sinks.
• Implement flow automation, routing, and transformation logic.
• Optimize performance, monitor operations, and troubleshoot issues.

Format of the Course

• Interactive lecture with real-world architecture discussion.
• Hands-on labs: building, deploying, and managing flows.
• Scenario-based exercises in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This training offers a hands-on introduction to creating scalable data processing and Machine Learning workflows using PySpark. Participants will gain insight into how Apache Spark functions within contemporary Big Data ecosystems and how to efficiently manage large datasets by leveraging distributed computing principles.

This instructor-led, live training in Brazil (online or onsite) is aimed at engineers who wish to set up and deploy Apache Spark system for processing very large amounts of data.

By the end of this training, participants will be able to:

• Install and configure Apache Spark.
• Quickly process and analyze very large data sets.
• Understand the difference between Apache Spark and Hadoop MapReduce and when to use which.
• Integrate Apache Spark with other machine learning tools.

This instructor-led live training in Brazil (online or onsite) is aimed at beginner to intermediate system administrators who wish to deploy, maintain, and optimize Spark clusters.

By the end of this training, participants will be able to:

• Install and configure Apache Spark in various environments.
• Manage cluster resources and monitor Spark applications.
• Optimize the performance of Spark clusters.
• Implement security measures and ensure high availability.
• Debug and troubleshoot common Spark issues.

The learning curve for Apache Spark can be steep at the beginning, requiring considerable effort to see initial results. This course is designed to help you navigate those early challenges effectively. Upon completion, participants will grasp the fundamentals of Apache Spark, clearly distinguish between RDDs and DataFrames, and become proficient with the Python and Scala APIs. You will also gain insights into how executors and tasks operate. Aligned with industry best practices, the course places a strong emphasis on cloud deployment, specifically focusing on Databricks and AWS environments. Additionally, students will learn to differentiate between AWS EMR and AWS Glue, exploring one of AWS's newer Spark services.

AUDIENCE:

Data Engineers, DevOps Professionals, Data Scientists

In this instructor-led, live training in Brazil, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.

By the end of this training, participants will be able to:

• Learn how to use Spark with Python to analyze Big Data.
• Work on exercises that mimic real world cases.
• Use different tools and techniques for big data analysis using PySpark.

This instructor-led, live training in Brazil (online or onsite) is aimed at developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets.

By the end of this training, participants will be able to:

• Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
• Understand the features, core components, and architecture of Spark and Hadoop.
• Learn how to integrate Spark, Hadoop, and Python for big data processing.
• Explore the tools in the Spark ecosystem (Spark MLlib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
• Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
• Use Apache Mahout to scale machine learning algorithms.

Stratio is a data-centric platform that combines big data, artificial intelligence, and governance into a unified solution. Its Rocket and Intelligence modules facilitate rapid data exploration, transformation, and advanced analytics within enterprise environments.

This instructor-led live training (available online or onsite) is designed for intermediate-level data professionals seeking to effectively utilize the Rocket and Intelligence modules in Stratio with PySpark. The course focuses on looping structures, user-defined functions, and advanced data logic.

Upon completing this training, participants will be able to:

• Navigate and operate within the Stratio platform using the Rocket and Intelligence modules.
• Apply PySpark for data ingestion, transformation, and analysis.
• Utilize loops and conditional logic to manage data workflows and perform feature engineering.
• Create and manage user-defined functions (UDFs) to enable reusable data operations in PySpark.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• Hands-on implementation in a live laboratory environment.

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.

This instructor-led live training in Brazil (online or onsite) is designed for system administrators, data scientists, and business analysts who wish to set up Talend Administration Center to deploy and manage the organization's roles and tasks.

Upon completion of this training, participants will be able to:

• Install and configure Talend Administration Center.
• Grasp and apply the fundamentals of Talend management.
• Create, deploy, and execute business projects or tasks in Talend.
• Monitor dataset security and develop business routines based on the TAC framework.
• Gain a deeper understanding of big data applications.

This instructor-led, live training in Brazil (online or onsite) is designed for beginner to intermediate-level data analysts who wish to enhance their understanding and skills in managing and improving data quality using Talend Data Stewardship.

By the end of this training, participants will be able to:

• Gain a comprehensive understanding of the role of data stewardship in maintaining data quality.
• Utilize Talend Data Stewardship for managing data quality tasks.
• Create, assign, and manage tasks within Talend Data Stewardship, including workflow customization.
• Use the tool's reporting and monitoring capabilities to track data quality and stewardship efforts.

In this instructor-led live training conducted in Brazil, participants will learn how to utilize Talend Open Studio for ESB to create, connect, mediate, and manage services and their interactions.

Upon completing this training, participants will be capable of:

• Integrating, enhancing, and deploying ESB technologies as unified packages across diverse deployment environments.
• Understanding and effectively using the most frequently utilized components of Talend Open Studio.
• Connecting any application, database, API, or web service.
• Seamlessly integrating heterogeneous systems and applications.
• Incorporating existing Java code libraries to extend project capabilities.
• Utilizing community-provided components and code to expand project functionality.
• Rapidly integrating systems, applications, and data sources within an intuitive drag-and-drop Eclipse-based environment.
• Reducing development time and maintenance costs through the generation of optimized, reusable code.