Talend Big Data Integration Training Course

This instructor-led, live training in Botswana (online or onsite) is tailored 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 an in-depth 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, perform complex schema changes, and handle partition evolution.
• Master techniques to optimize 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 Botswana (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 Botswana (online or onsite) is designed for data scientists and engineers at an intermediate level who wish to utilise Google Colab and Apache Spark for big data processing and analytics.

Upon completing this training, participants will be able to:

• Establish a big data environment using Google Colab and Spark.
• Process and analyse large datasets efficiently with Apache Spark.
• Visualise big data within 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 constructing scalable data processing and Machine Learning workflows using PySpark. Participants will gain insight into how Apache Spark functions within contemporary Big Data ecosystems and learn to process large datasets efficiently by applying distributed computing principles.

This instructor-led, live training in Botswana (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 Botswana (online or onsite) is aimed at beginner to intermediate system administrators who wish to deploy, maintain, and optimise 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 initial learning curve for Apache Spark can be steep, requiring considerable effort before seeing tangible results. This course is designed to help you surmount that early hurdle. Upon completion, participants will grasp the fundamentals of Apache Spark, clearly distinguish between RDDs and DataFrames, gain proficiency in both Python and Scala APIs, and comprehend the roles of executors and tasks. Furthermore, adhering to industry best practices, the course places strong emphasis on cloud deployment, with specific focus on Databricks and AWS. Students will also learn to differentiate between AWS EMR and AWS Glue, one of AWS's most recent Spark-related services.

AUDIENCE:

Data Engineers, DevOps Professionals, Data Scientists

In this instructor-led, live training in Botswana, participants will learn how to use Python and Spark together to analyze big data while working 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 Botswana (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 unified platform that brings together big data, artificial intelligence, and governance. Through its Rocket and Intelligence modules, it facilitates swift data exploration, transformation, and advanced analytics for enterprise settings.

This instructor-led live training, available online or onsite, is designed for intermediate data professionals keen on leveraging the Rocket and Intelligence modules within Stratio using PySpark. The focus is on mastering looping structures, user-defined functions, and sophisticated data logic.

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

• Navigate and operate within the Stratio platform, utilising its Rocket and Intelligence modules.
• Apply PySpark effectively for data ingestion, transformation, and analysis.
• Employ loops and conditional logic to manage data workflows and feature engineering tasks.
• Develop and manage user-defined functions (UDFs) to facilitate reusable data operations in PySpark.

Course Format

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

Customisation Options

• To arrange a tailored training session for this course, please contact us.

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

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

• Install and configure Talend Administration Center.
• Understand and implement Talend management fundamentals.
• Build, deploy, and run business projects or tasks in Talend.
• Monitor the security of datasets and develop business routines based on the TAC framework.
• Obtain a broader comprehension of big data applications.

This instructor-led live training in Botswana (available online or onsite) is designed for data analysts at beginner to intermediate levels who wish to deepen their understanding and skills in managing and improving data quality using Talend Data Stewardship.

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

• Develop a thorough understanding of the role data stewardship plays in maintaining data quality.
• Utilise Talend Data Stewardship to oversee data quality tasks.
• Create, assign, and manage tasks within Talend Data Stewardship, including the customisation of workflows.
• Leverage the tool’s reporting and monitoring features to track data quality and stewardship activities.

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

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

• Integrate, enhance, and deliver ESB technologies as single packages in a variety of deployment environments.
• Understand and utilize the most commonly used components of Talend Open Studio.
• Integrate any application, database, API, or Web services.
• Seamlessly integrate heterogeneous systems and applications.
• Embed existing Java code libraries to extend projects.
• Leverage community components and code to extend projects.
• Rapidly integrate systems, applications, and data sources within a drag-and-drop Eclipse environment.
• Reduce development time and maintenance costs by generating optimized, reusable code.