Nairobi, Kenya

254721214795

Advanced Big Data Engineering with Scala

This advanced training provides participants with practical knowledge and skills to design, build, and optimize scalable big data architectures using Scala. The course explores Scala's role in distrib...

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ONSITE OR VIRTUAL

3 upcoming sessions in the next 3 months

Oct 26 - Oct 30
Nov 23 - Nov 27
Dec 28 - Jan 01
Programme Overview
Training Description

Who Should Attend

  • Software engineers
  • Data architects
  • Cloud engineers
  • Data scientists
  • Analytics professionals
  • Database professionals
  • Machine learning engineers
  • Enterprise architects
  • Technology and IT managers
  • Business intelligence professionals
  • DevOps and platform engineers
  • Professionals involved in large-scale data processing and digital transformation
 
 
 
Session Objectives
  • Understand the fundamentals of Scala for Big Data development.
  • Master Spark with Scala (Spark Scala) for distributed data processing.
  • Utilize Akka for building concurrent and distributed systems.
  • Implement advanced functional programming techniques in Scala.
  • Design and build scalable Big Data applications with Scala.
  • Optimize Scala code for performance and efficiency.
  • Troubleshoot and debug Scala Big Data applications.
  • Implement data security and access control in Scala data workflows.
  • Integrate Scala with various Big Data platforms.
  • Understand how to monitor and maintain Scala Big Data systems.
  • Explore advanced Scala patterns and techniques for Big Data.
  • Apply real world use cases for Scala in Big Data development.
  • Leverage Scala for building real-time data processing applications.
About the Course


This advanced training provides participants with practical knowledge and skills to design, build, and optimize scalable big data architectures using Scala. The course explores Scala's role in distributed data processing, with a strong focus on building efficient, reliable, and maintainable data solutions for large-scale enterprise environments.Participants will learn how to work with Scala-based data processing frameworks, design distributed data pipelines, manage large datasets, optimize Spark workloads, and implement scalable data architectures. The training combines Scala programming concepts with big data engineering practices, enabling participants to develop solutions capable of handling high-volume, high-velocity, and complex data workloads.

Curriculum & Topics

15 Topics | 71 Sessions

  • play Workshop 1.1: Fundamentals of Scala for Big Data.

  • play Workshop 1.2: Overview of Scala's advantages for Big Data processing.

  • play Workshop 1.3: Setting up a Scala Big Data development environment.

  • play Workshop 1.4: Introduction to Scala concepts and syntax.

  • play Workshop 1.5: Best practices for Scala Big Data development.

  • play Workshop 2.1: Utilizing Spark with Scala for distributed data processing.

  • play Workshop 2.2: Implementing Spark DataFrames and Datasets.

  • play Workshop 2.3: Designing and building Spark applications in Scala.

  • play Workshop 2.4: Optimizing Spark applications for performance.

  • play Workshop 2.5: Best practices for Spark Scala.

  • play Workshop 3.1: Utilizing Akka for building concurrent and distributed systems.

  • play Workshop 3.2: Implementing Akka Actors and Streams.

  • play Workshop 3.3: Designing and building Akka applications for Big Data.

  • play Workshop 3.4: Optimizing Akka applications for performance.

  • play Workshop 3.5: Best practices for Akka.

  • play Workshop 4.1: Implementing advanced functional programming concepts.

  • play Workshop 4.2: Utilizing higher-order functions and pattern matching.

  • play Workshop 4.3: Implementing functional data structures.

  • play Workshop 4.4: Designing and building functional data pipelines.

  • play Workshop 4.5: Best practices for functional programming.

  • play Workshop 5.1: Designing scalable Big Data applications with Scala.

  • play Workshop 5.2: Utilizing Scala best practices for building robust systems.

  • play Workshop 5.3: Implementing microservices architecture with Scala.

  • play Workshop 5.4: Optimizing application performance and resource utilization.

  • play Workshop 5.5: Best practices for scalable application design.

  • play Workshop 6.1: Optimizing Scala code for performance and efficiency.

  • play Workshop 6.2: Utilizing profiling and benchmarking tools.

  • play Workshop 6.3: Implementing concurrency and parallelism in Scala.

  • play Workshop 6.4: Designing efficient data processing pipelines.

  • play Workshop 6.5: Best practices for performance optimization.

  • play Workshop 7.1: Debugging Scala Big Data applications.

  • play Workshop 7.2: Analyzing performance and data issues.

  • play Workshop 7.3: Utilizing debugging tools and techniques.

  • play Workshop 7.4: Resolving common Scala Big Data problems.

  • play Workshop 7.5: Best practices for troubleshooting.

  • play Workshop 8.1: Implementing data security in Scala data workflows.

  • play Workshop 8.2: Utilizing authentication and authorization.

  • play Workshop 8.3: Implementing data encryption and masking.

  • play Workshop 8.4: Managing data permissions and privileges.

  • play Workshop 8.5: Best practices for data security.

  • play Workshop 9.1: Integrating Scala with various Big Data platforms.

  • play Workshop 9.2: Utilizing data connectors and APIs.

  • play Workshop 9.3: Implementing data transfer between Scala and Big Data systems.

  • play Workshop 9.4: Best practices for integration.

  • play Workshop 10.1: Monitoring Scala Big Data systems.

  • play Workshop 10.2: Implementing alerting and notifications.

  • play Workshop 10.3: Utilizing monitoring tools and techniques.

  • play Workshop 10.4: Managing Scala Big Data applications.

  • play Workshop 10.5: Best practices for monitoring.

  • play Workshop 11.1: Implementing advanced Scala patterns for Big Data.

  • play Workshop 11.2: Utilizing Scala for building streaming applications.

  • play Workshop 11.3: Implementing advanced concurrency patterns.

  • play Workshop 11.4: Advanced techniques for Scala Big Data development.

  • play Workshop 11.5: Best practices for advanced patterns.

  • play Workshop 12.1: Implementing Scala for ETL pipelines.

  • play Workshop 12.2: Utilizing Scala for building data warehousing applications.

  • play Workshop 12.3: Implementing Scala for machine learning pipelines.

  • play Workshop 12.4: Utilizing Scala for real-time data analysis.

  • play Workshop 12.5: Best practices for real world applications.

  • play Workshop 13.1: Deploying Scala Big Data applications on cloud platforms.

  • play Workshop 13.2: Utilizing cloud-based Scala libraries and services.

  • play Workshop 13.3: Optimizing cloud resources for Scala applications.

  • play Workshop 13.4: Best practices for cloud deployment.

  • play Workshop 14.1: Implementing data governance policies in Scala data workflows.

  • play Workshop 14.2: Utilizing metadata management for Scala data.

  • play Workshop 14.3: Implementing data lineage and data dictionary.

  • play Workshop 14.4: Best practices for data governance.

  • play Workshop 15.1: Emerging trends in Scala for Big Data.

  • play Workshop 15.2: Utilizing AI and automation in Scala data pipelines.

  • play Workshop 15.3: Implementing serverless Scala data applications.

  • play Workshop 15.4: Best practices for future Scala development.

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$ 2,000


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This Programme Includes

Certificate of completion

Training manual

Reference materials

10 o'clock tea

Lunch

4 o'clock tea

Course Highlights
  • icon 10 Days Intensive Training

  • icon 15 Core Learning Topics

  • icon 71 Professional Sessions

  • icon Unknown Expert-led Delivery

FAQs

Frequently Asked Questions

Explore detailed answers to the most common questions about our platform and services.

What are the payment terms and methods?

Payments can be made via bank transfer or bank draft payable to PB Institute of Research and Technology. For corporate-sponsored participants, a formal undertaking/Local Purchase Order (LPO) from the employer is required to secure a slot before the training commencement date.

Our primary residential and corporate training programs are hosted in premium, fully equipped conference facilities in Nairobi, Kenya. We also coordinate regional and international training locations depending on the specific cohort and organizational requirements. Exact venue details are communicated in your admission letter.

If you are unable to attend, you must notify us in writing at least 7 days before the course start date. You may choose to nominate a qualified substitute colleague at no additional cost or defer your enrolment to the next scheduled cohort for that program.

While the majority of our intensive professional programs are structured for high-engagement, on-site delivery, we offer select courses in a virtual or hybrid format. If your organization requires online delivery for a specific module, please indicate this during your booking inquiry.

Yes. Participants who successfully complete a training program and meet the minimum attendance requirements will be awarded a globally recognized Certificate of Proficiency from the Pebbles Institute of Research and Technology.

Most of our professional short courses are structured as intensive 5- or 10-day programs to minimize extended workplace absence while maximizing skill acquisition. We also offer compressed 1-to-3-day masterclasses.