Data Warehouse Modelling
This program teaches you how to build and optimize data warehouses for powerful insights.In seven sessions, you'll learn about things like data structure, designing tables, and how to move and transform data using ODI. We'll also look at real-life examples to connect what you learn with practical work.After completing the bootcamp, you'll be ready for various career paths, including jobs like Data Warehouse Developer, Business Intelligence Analyst, Data Engineer, Database Administrator, Data Consultant, and more. This course opens doors to exciting careers in the world of data.
Training table
Information about the training
The Oracle Data Integrator (ODI) Data Warehouse Modeling Bootcamp is your gateway to mastering the art of designing, building, and optimizing data warehouses. Throughout this course, you will explore foundational concepts such as dimensional modeling, fact table design, and the intricacies of slowly changing dimensions (SCD), dive into the world of ETL/ELT processes using ODI and learn best practices for performance optimization. Additionally, you'll gain hands-on experience through practical case studies, where you'll define business goals, design data warehouse architectures, and create ETL/ELT pipelines. The course also extends your knowledge to encompass other databases like PostgreSQL and MySQL, providing a well-rounded understanding of database management.By the end of this bootcamp, you'll have a comprehensive skill set to tackle real-world data warehousing challenges effectively.
Who is this training for?
- Students
- Software developers
- Data science specialists
- Database administrators
- Researchers and academics
Certificate
It provides a certificate to those who complete the training as Certified Data Scientist and others. You can see a sample certificate on the right.
Database vs Data Warehouse vs Data Lake
Database vs Data Warehouse vs Data Lake
Alex The Analyst
we take a look at these 3 different ways to store data and the differences between them.
Syllabus
Session 1
OLAP and OLTP databases
Kimball and Inmon theory
Dimensional Modeling Tools and Techniques
Role-playing, Junk, Degenerate, Conformed Dimensions
Hierarchies in dimensions
Nulls in dimensions
Case Study 1
Designing the Data Schema for the Data Warehouse of an E-commerce Company
Session 2
Fact table design
Star Schema
Snowflake Schema
Slowly Changing Dimension (SCD) models
Introduction to SCD
SCD Types
Hybrid SCD Approaches
Case Study 2
Designing the fact tables and slowly changing dimensions of the healthcare organization’s data warehouse
Session 3
Fact table loading
Data Extraction
Data Transformation
Fact Table Populating Techniques
Dimension table loading
Type 1 Dimension Loading
Type 2 Dimension Loading
Case Study 3
Loading of fact and dimension tables of a technical company
Session 4
Introduction to Oracle Data Integrator (ODI)
Building ETL Pipelines in ODI
Staging Area, Data Marts, Cubes
Initial, Delta Loads
Best Practices and Performance Optimization
Case Study 4
Developing ETL pipelines for a Retail Company
Session 5
ELT ODI
ELT Pipelines in Oracle Data Integrator
Introduction to ELT Pipelines
Difference between ETL and ELT
Building ELT Pipelines in ODI
Case Study 5
Let's consider a case study involving a fictional organization called "TechCo." TechCo is a technology company that operates various online platforms and wants to implement ELT pipelines in Oracle Data Integrator to load and transform data efficiently.
Scenario: Implementing ELT pipelines in the DWH of a technology company
Sessiya 6
Practical case of building Data Warehouse
Define Business Goals and Requirements
Design the Data Warehouse Architecture
ETL/ELT pipelines
Build and Populate Dimensional and Fact Tables
Case Study 6
Developing Data Warehouse
Session 7
Other databases (PostgreSQL, MySQL)
Overview of PostgreSQL
Overview of MySQL
Connecting to SQL databases using Python
Case Study 7
Connecting to the PostgreSQL database of an Online Retail Company using Python
Trainers
Bahruz Gasimov
EXPERT FOR DATA QUALITY AND ASSURANCE MANAGEMENT, PASHA BANKOur professional trainer Bahruz Gasimov currently works as an “Expert in Data Quality and Assurance Management” at Pasha Bank. He has also worked in the data field at companies such as TuranBank OJSC, Yapı Kredi Bank Azerbaijan, and Unibank, and has over 14 years of professional work experience.