Big Data Architect


Workshops not currently scheduled

We are currently planning the workshops for this course. You may purchase an eLearning kit for immediate access or contact us for further details.

USD $937.73 $468.86 eLearning Kit only

Big Data is big business. There are quintillion bytes of data being generated every day. While companies are using Big Data Science to sift through this avalanche of data and find the information that is relevant to the needs of the company, it is the role of the IT Professionals to build the architecture that supports this process. In this course, you will learn the mechanisms, approaches and design patterns that are used to architect Big Data solutions.

Get a sample of the contents of this course with this short video lesson that provides a non-technical introduction to Big Data Analysis. This second video lesson is an introduction to Big Data Analytics. Both of these topics are part of Module 1 of the course.

The eLearning kit bundle provides access to a 5 Module course bundle that will be available for 1 year from the date of purchase. The course outline is provided in the Details tab, you can also download a pdf version here. You can also take the on-line exam to get a Digital Badge to show your expertise in this field.

Course contents: 5 Modules

  • Module 1: Fundamental Big Data
  • Module 2: Big Data Analysis & Technology Concepts
  • Module 10: Fundamental Big Data Architecture
  • Module 11: Advanced Big Data Architecture
  • Module 12: Big Data Architecture Lab


Intended for
IT Professionals, Solution Architects, Enterprise Architects, Big Data specialists


An understanding of IT concepts and IT architecture is required for this course.


Learning Outcomes

A comprehensive understanding of the approaches, design patterns and the mechanisms that are essential for architecting Big Data systems. Some of the topics covered include:

  • Fundamental Terminology and Concepts
  • Basic Big Data Analytics
  • Big Data and Traditional Business Intelligence and Data Warehouses
  • Common Analysis and Analytics Techniques
  • Automated Recommendation, Classification, Clustering
  • Machine Language, Natural Language, Semantics
  • Big Data Technology Mechanisms
  • Big Data Storage (Query Workload, Sharding, Replication, CAP, ACID, BASE)
  • Big Data Processing
  • New Big Data Mechanisms
  • Enterprise Data Warehouse and Big Data Integration Approaches
  • Architectural Big Data Environments
  • Cloud Computing & Big Data Architectural Considerations
  • Big Data Solution Architectural Layers
  • Big Data Solution Design Patterns
  • Big Data Architectural Compound Patterns

And more

 Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

Module 1 Fundamental Big Data

A foundational course that establishes a basic understanding of Big Data from business and technology perspectives, including common benefits, challenges and adoption issues.

The following primary topics are covered: 

•Fundamental Terminology and Concepts
•A Brief History of Big Data
•Business Drivers that Have Led to Big Data Innovations
•Characteristics of Big Data•Benefits of Adopting Big Data
•Challenges and Limitations of Big Data
•Basic Big Data Analytics
•Big Data and Traditional Business Intelligence and Data Warehouses
•Big Data Visualization
•Common Adoption Issues
•Planning for Big Data Initiatives
•New Roles Introduced by Big Data Projects
•Emerging Trends

Module 2 Big Data Analysis & Technology Concepts

Explores contemporary analysis practices, technologies, and tools for Big Data environments at a conceptual level, focusing on common analysis functions and features of Big Data solutions.

The following primary topics are covered:

•The Big Data Analysis Lifecycle (from dataset identification to integration, analysis, and visualization)
•Common Analysis and Analytics Techniques•A/B testing, Regression, Correlation, Text Analytics
•Sentiment Analysis, Time Series Analysis
•Network Analysis, Spatial Analysis
•Automated Recommendation, Classification, Clustering
•Machine Language, Natural Language, Semantics
•Data Visualization and Visual Analysis
•Assessing Hierarchies, Part-to-Whole Relationships
•Plotting Connections and Relationships, Mapping Geo-Spatial Data
•Foundational Big Data Technology Mechanisms
•Big Data Storage (Query Workload, Sharding, Replication, CAP, ACID, BASE)
•Big Data Processing (Parallel Data Processing, Distributed Data Processing, SharedEverything/Nothing Architecture, SCV)

Module 10 Fundamental Big Data Architecture

Coverage of the Hadoop stack, data pipelines and other technology architecture layers, mechanisms and components, and associated design patterns.

The following primary topics are covered:

•New Big Data Mechanisms, including Security Engine, Cluster Manager, Data Governance Manager, Visualization Engine and Productivity Portal
•Data Processing Architectural Models, including Shared-Everything and SharedNothing Architectures
•Enterprise Data Warehouse and Big Data Integration Approaches, including Series, Parallel, Big Data Appliance and Data Virtualization
•Architectural Big Data Environments, including ETL, Analytics Engine and Application Enrichment
•Cloud Computing & Big Data Architectural Considerations, including how Cloud Delivery and Deployment Models can be used to host and process Big Data Solutions (and resulting issues and risks)

Module 11 Advanced Big Data Architecture

Drill-down of Big Data solution environments, additional advanced design patterns, and coverage of cloud implementations and various enterprise integration considerations.

The following primary topics are covered:

•Big Data Solution Architectural Layers including Data Sources, Data Ingress and Storage, Event Stream Processing and Complex Event Processing, Egress, Visualization and Utilization, Big Data Architecture and Security, Maintenance and Governance
•Big Data Solution Design Patterns, including patterns pertaining to Data Ingress, Data Wrangling, Data Storage, Data Processing, Data Analysis, Data Egress, Data Visualization and more
•Big Data Architectural Compound Patterns

Module 12 Big Data Architecture Lab

A hands-on lab during in which a set of real-world exercises challenge participants to build and integrate Big Data solutions within IT enterprise and cloud-based environments.

This course module covers a series of exercises and problems designed to test the participant’s ability to apply knowledge of topics covered previously in course modules 10 and 11. Completing this lab will help highlight areas that require further attention, and will further prove hands-on proficiency in Big Data architecture practices as they are applied and combined to solve real-world problems.

As a hands-on lab, this course incorporates a set of detailed exercises that require participants to solve various inter-related problems, with the goal of fostering a comprehensive understanding of how different data architecture technologies, mechanisms, and techniques can be applied to solve problems in Big Data environments. 


Exams & Certification

  • Those that pass the exams required for the Certified Big Data Architect designation will receive official certificate for this designation and will have access to the benefits associated with this certification.
  • The exams required for certification can be taken at any Pearson VUE testing center in the world or online via Pearson VUE Online Proctoring.


Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

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