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Online Course
free
Introduction to Data Architecture
with
Rahul Singh
Want to excel in data architecture? Our data architecture course equips you with the fundamentals, best practices, and hands-on skills to design scalable, modern data systems.
1756 students already have enrolled
Skill level:
Basic
Duration:
1 hour
-
Lessons (3 hours)
- Lessons (3 hours)
CPE credits:
5
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
Accredited:
certificate
What You Learn
- Design and build scalable and efficient data architectures.
- Master data modeling techniques like ERDs, normalization, dependencies, etc.
- Understand storage systems, including data lakes, warehouses, and lakehouses.
- Build robust batch and real-time data pipelines using ETL/ELT.
- Explore modern data architecture technologies like AI/ML, blockchain, and IoT.
Topics & tools
data architecturedata modelingcloud computingdata engineeringtheory
Your instructor
Product Manager | Data Systems at Bloomberg | AI & Cloud Expert
Track record
Bringing real-world expertise from leading global companies
Academic background
Master's degree, Data Science
Course OVERVIEW
Description
CPE Credits: 5
Field of Study: Information Technology
Delivery Method: QAS Self Study
Delivery Method: QAS Self Study
Step into the world of modern data architecture with this hands-on training. Designed for data professionals, technologists, and aspiring architects, this in-depth data architecture course helps you create and manage scalable, efficient data systems.
What’s included in the curriculum?
- Foundations of Data Architecture: Understand data architecture principles, key components, and types of architectures—including centralized, decentralized, and hybrid approaches.
- Data Storage and Management: Explore relational databases, NoSQL, data lakes, metadata management, and data governance best practices.
- Data Modeling: Master conceptual, logical, and physical modeling—including ERDs, normalization, and performance optimization.
- Data Integration: Learn real-time and batch processing, ETL/ELT pipelines, and frameworks like Apache Kafka and Spark.
- Emerging Technologies: Stay ahead with cloud-native architectures, Data Mesh, Data Fabric, edge computing, IoT, and blockchain.
By the end of this data architect training, you will:
- Have the confidence to design modern data architectures from scratch
- Integrate advanced tools and emerging technologies
- Ensure scalability, efficiency, and future-readiness in data systems
- Be equipped with industry best practices to enhance data-driven decision-making
Why should you enroll in a data architecture course?
- Data-driven organizations are 23x more likely to acquire customers and 19x more profitable.
- Poor data quality costs US businesses over $3.1 trillion annually.
- Skilled data architects are in high demand, with salaries ranging from $120K to $180K annually.
Whether aiming for a data architect certification or upgrading existing systems, this course is your step-by-step guide to mastering data architecture best practices. Enroll in this data architecture course now to start your learning journey!
Prerequisites
- Basic understanding of data concepts (such as databases, tables, or files) is helpful but not required.
Advanced preparation
Curriculum
31 lessons
30 exercises
1 exam
- 2. Foundations of Data Architecture23 Min
In this data architecture training, you’ll deeply grasp key principles, architecture types, and best practices. You’ll also discover how to align data strategies with business goals and effectively integrate technical and business architecture.
- 3. Data Storage and Management37 Min
Master data storage systems like relational databases, NoSQL, data lakes, and warehouses. Learn metadata and master data management (MDM), governance principles, security considerations, and techniques to ensure data quality and compliance.
- 4. Data Modeling and Design Principles47 Min
Develop expertise in physical, conceptual, and logical modeling. Learn to create ERDs, handle normalization and denormalization, and optimize data models for scalability. This section also covers data-driven solutions for enhancing system efficiency.
Introduction to Data Modeling FreeData Relationships and Dependencies FreeExercise FreeDesigning Entity Relationship Diagrams FreeTypes of Data Models FreeExercise FreeData Normalization and Normal Forms FreeData Denormalization FreeExercise FreeScalability and Performance Optimization FreeExercise Free - 5. Data Integration24 Min
This section of our Data Architecture course explores real-time and batch processing techniques, data pipelines, and streaming architectures. Explore ETL/ELT processes, big data frameworks like Hadoop and Spark, and strategies for integrating data across systems to ensure seamless operations and analytics.
- 6. Designing for the Future46 Min
Explore modern data architectures like cloud-native systems, Data Mesh, and Data Fabric. Dive into emerging technologies, including blockchain, IoT, edge computing, and AI/ML integration for intelligent data-driven solutions.
Cloud-Native Data Architectures FreeBuilding a Cloud-Native E-Commerce Architecture FreeExercise FreeModern Data Architecture Patterns FreeData Warehouse vs. Data Lake vs. Data Lakehouse FreeExercise FreeAI and ML in Data Architecture FreeEmerging Technologies: Edge Computing and Blockchain FreeEmerging Technologies: Data Mesh vs. Data Fabric FreeExercise Free - 7. Hands-On Data Architecture Design22 Min
Apply your knowledge by designing a complete data architecture for a real-world business scenario. This final project combines all concepts—from defining requirements and creating blueprints to implementing systems and evaluating performance optimization.
- 8. Course exam45 Min
Free preview
1.1 Introduction to the Course
1 min
1.2 What Does the Course Cover
3 min
2.1 What is Data Architecture
5 min
2.2 Key Principles and Components
7 min
2.4 Types of Data Architecture
11 min
9 in 10
of our graduates landed a new AI & data job
after enrollment
96%
of our students recommend
365 Data Science.
94%
of AI and data science graduates
successfully change
or advance their careers.
ACCREDITED certificates
Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global
institutions.
Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities
employers value most.
How it WORKS
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