COURSE OVERVIEW:
Welcome to the course on Build Data Warehouses. This course is designed to provide you with the foundational knowledge and practical skills needed to design, implement, and manage data warehouses effectively, enabling robust data analytics and business intelligence capabilities.
We begin with an introduction to data warehousing, defining what a data warehouse is and explaining its importance in today’s data-driven business environment. This section will cover key concepts and terminology essential for understanding data warehousing fundamentals.
Next, we explore data warehousing architecture. You will gain an overview of different data warehouse architectures, including centralised, distributed, and cloud-based architectures. We will also discuss the various components that make up data warehousing systems, providing a comprehensive understanding of their structure and functionality.
Requirements gathering and analysis are crucial for building an effective data warehouse. This section will guide you through identifying business requirements, conducting data requirements analysis, and using stakeholder interviews and workshops to gather essential information.
Data modelling for data warehousing is a critical step in the design process. We will cover conceptual, logical, and physical data models, as well as different schema designs such as star schema and snowflake schema. Understanding fact and dimension tables will also be a focus in this section.
The ETL (Extract, Transform, Load) process is at the heart of data warehousing. You will learn about the ETL process, the tools commonly used (such as Informatica, Talend, and SSIS), and how to design and implement effective ETL workflows to ensure accurate and efficient data processing.
Data integration techniques are essential for combining data from various sources. This section will explore methods for data integration, comparing real-time versus batch integration, and discussing data cleaning and transformation techniques to ensure high-quality data.
Data storage and management are vital for the performance and scalability of a data warehouse. We will discuss choosing the right storage solutions, including on-premise and cloud options, and cover data partitioning, indexing, and strategies for managing data growth and scalability.
Ensuring data quality and governance is crucial for maintaining the integrity of your data warehouse. This section will cover methods for ensuring data accuracy and consistency, tools for data quality management, and how to implement effective data governance policies.
Performance tuning and optimisation are necessary to maintain efficient data warehouse operations. You will learn query optimisation techniques, indexing strategies, and methods for performance monitoring and maintenance to ensure your data warehouse runs smoothly.
Security and compliance are essential considerations in data warehousing. This section will cover best practices for data security, implementing access controls, and ensuring compliance with Australian regulations to protect sensitive data.
Reporting and analytics are the primary outputs of a data warehouse. We will explore tools for reporting and visualisation, such as Tableau and Power BI, and discuss how to design effective reports and dashboards. Advanced analytics and data mining techniques will also be introduced.
Data warehousing in the cloud offers numerous benefits. This section will discuss the advantages of cloud data warehousing, review major cloud platforms (AWS Redshift, Google BigQuery, Azure Synapse), and provide guidance on migrating to a cloud data warehouse.
Finally, maintenance and administration are key to the long-term success of your data warehouse. We will cover regular maintenance tasks, backup and recovery procedures, and methods for monitoring and troubleshooting to ensure continuous and reliable data warehouse operations.
By the end of this course, you will have a comprehensive understanding of how to build and manage data warehouses, enabling your organisation to leverage data for strategic decision-making and competitive advantage.
LEARNING OUTCOMES:
By the end of this course, you will be able to understand the following topics:
1. Introduction to Data Warehousing
- Definition and Importance of Data Warehousing
- Key Concepts and Terminology
2. Data Warehousing Architecture
- Overview of Data Warehouse Architecture
- Types of Data Warehouse Architectures (Centralised, Distributed, Cloud)
- Components of Data Warehousing Systems
3. Requirements Gathering and Analysis
- Identifying Business Requirements
- Data Requirements Analysis
- Stakeholder Interviews and Workshops
4. Data Modelling for Data Warehousing
- Conceptual, Logical, and Physical Data Models
- Star Schema and Snowflake Schema
- Fact and Dimension Tables
5. ETL (Extract, Transform, Load) Processes
- Overview of ETL Processes
- Tools for ETL (Informatica, Talend, SSIS)
- Designing and Implementing ETL Workflows
6. Data Integration Techniques
- Data Integration Methods
- Real-Time vs. Batch Integration
- Data Cleaning and Transformation
7. Data Storage and Management
- Choosing the Right Storage Solution (On-Premise, Cloud)
- Data Partitioning and Indexing
- Managing Data Growth and Scalability
8. Data Quality and Governance
- Ensuring Data Accuracy and Consistency
- Data Quality Management Tools
- Implementing Data Governance Policies
9. Performance Tuning and Optimisation
- Query Optimisation Techniques
- Indexing Strategies
- Performance Monitoring and Maintenance
10. Security and Compliance
- Data Security Best Practices
- Implementing Access Controls
- Compliance with Australian Regulations
11. Reporting and Analytics
- Tools for Reporting and Visualisation (Tableau, Power BI)
- Designing Effective Reports and Dashboards
- Advanced Analytics and Data Mining
12. Data Warehousing in the Cloud
- Benefits of Cloud Data Warehousing
- Cloud Platforms for Data Warehousing (AWS Redshift, Google BigQuery, Azure Synapse)
- Migrating to a Cloud Data Warehouse
13. Maintenance and Administration
- Regular Maintenance Tasks
- Backup and Recovery Procedures
- Monitoring and Troubleshooting
COURSE DURATION:
The typical duration of this course is approximately 2-3 hours to complete. Your enrolment is Valid for 12 Months. Start anytime and study at your own pace.
COURSE REQUIREMENTS:
You must have access to a computer or any mobile device with Adobe Acrobat Reader (free PDF Viewer) installed, to complete this course.
COURSE DELIVERY:
Purchase and download course content.
ASSESSMENT:
A simple 10-question true or false quiz with Unlimited Submission Attempts.
CERTIFICATION:
Upon course completion, you will receive a customised digital “Certificate of Completion”.