Fundamental Big Data Architecture

Module 10
Fundamental Big Data Architecture

This course provides an overview of the fundamental and essential topic areas pertaining to Big Data solution platform architecture, introducing several new Big Data mechanisms and covering a range of architectural models, approaches and considerations. Specifically, it covers Big Data mechanisms required for the development of a Big Data solution platform and architectural options for assembling a data processing platform. It further introduces the enterprise data warehouse and discusses various options for its integration with the Big Data solution platform. Common scenarios are also presented to provide a basic understanding of how a Big Data solution platform is generally used. Finally, the use of cloud environment for the development of the Big Data solution platform is explored in the context of cloud computing delivery and deployment models.

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 Shared-Nothing 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)

Duration: 1 Day

Taking the Course at a Workshop

This course can be taken as part of public or private instructor-led workshops. Visit the Workshop Calendar page to view the current calendar of public workshops or contact to inquire about private workshop delivery.

The following materials are provided to public and private workshop participants:

Note that as a workshop participant, you may be eligible for discounts on the purchase of the self-study kit and Pearson VUE exam voucher for this course.

Taking the Course using a Self-Study Kit

This course can be completed via self-study by purchasing a self-study kit, which includes the base course materials as well as additional supplements and resources designed specifically for self-paced study and exam preparation.

Fundamental Big Data Architecture Module 10 Self-Study Kit [ order ]

Visit the Self-Study Kits page for pricing information and for details regarding discounted self-study kit bundles for individual certification tracks. The following materials are provided in the self-study kit for this course:


This self-study kit can be purchased using the Online Store.

Note that by purchasing and registering this self-study kit, you may be eligible for discounts on the registration of this course as part of a workshop.


This course corresponds to Exam B90.10, which is required for the following certifications:

Vendor-Neutral Topic Overview

Note that all BDSCP course modules are focused on vendor-neutral Big Data topics and therefore do not provide detailed coverage of any vendor-specific platforms or technologies. BDSCP courses are intentionally authored this way so as to provide an unambiguous and objective understanding of Big Data practices and technology that can be further complemented with product-specific training.

Fact Sheet

Download a printable PDF document with information about this course module and its corresponding self-study kit.

Pearson VUE Exams

A self-study kit is available for each Pearson VUE exam:

Self-Study Kits

A self-study kit is available for each Pearson VUE exam, allowing you to study remotely and at your own pace. For information about the latest available Self-Study Kits, visit the Self-Study page.

Instructor-Led Workshops

The following public workshops are currently scheduled. Additional workshops are often added on short notice. For information regarding private instructor-led workshops delivered to your location, contact: