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Data Warehouse Concepts, Design, and Data Integration

Approx. 22 hours to complete

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Course Summary

Learn how to design and develop databases that can handle large amounts of data with efficiency and ease. This course covers the fundamentals of database design and architecture, as well as best practices for data warehousing and data mining.

Key Learning Points

Understand the principles of database design and architecture
Learn how to optimize database performance for large amounts of data
Explore various data warehousing and data mining techniques

Learning Outcomes

Design and develop efficient databases that can handle large amounts of data
Optimize database performance for faster query times and improved user experience
Apply data warehousing and data mining techniques to extract insights from your data

Prerequisites or good to have knowledge before taking this course

Basic understanding of SQL
Familiarity with database management systems

Course Difficulty Level

Intermediate

Course Format

Online self-paced course
Video lectures and quizzes

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Data Warehousing for Business Intelligence
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Notable People in This Field

Statistician and Founder of FiveThirtyEight
Data Scientist and Founder of Fast Forward Labs

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Description

This is the second course in the Data Warehousing for Business Intelligence specialization. Ideally, the courses should be taken in sequence.

In this course, you will learn exciting concepts and skills for designing data warehouses and creating data integration workflows. These are fundamental skills for data warehouse developers and administrators. You will have hands-on experience for data warehouse design and use open source products for manipulating pivot tables and creating data integration workflows. In the data integration assignment, you can use either Oracle, MySQL, or PostgreSQL databases. You will also gain conceptual background about maturity models, architectures, multidimensional models, and management practices, providing an organizational perspective about data warehouse development. If you are currently a business or information technology professional and want to become a data warehouse designer or administrator, this course will give you the knowledge and skills to do that. By the end of the course, you will have the design experience, software background, and organizational context that prepares you to succeed with data warehouse development projects. In this course, you will create data warehouse designs and data integration workflows that satisfy the business intelligence needs of organizations. When you’re done with this course, you’ll be able to: * Evaluate an organization for data warehouse maturity and business architecture alignment; * Create a data warehouse design and reflect on alternative design methodologies and design goals; * Create data integration workflows using prominent open source software; * Reflect on the role of change data, refresh constraints, refresh frequency trade-offs, and data quality goals in data integration process design; and * Perform operations on pivot tables to satisfy typical business analysis requests using prominent open source software

Outline

Data Warehouse Concepts and Architectures
Course introduction video lecture
Course objectives video lecture
Course topics and assignments video lecture
Motivation and characteristics video lecture
Learning effects for data warehouse development video lecture
Data warehouse architectures and maturity video lecture
Data Warehouse Examples video lecture
Employment opportunities video lecture
Powerpoint lecture notes for lesson 1
Optional textbook
Powerpoint lecture notes for lesson 2
Powerpoint lecture notes for lesson 3
Powerpoint lecture notes for lesson 4
Powerpoint lecture notes for lesson 5
Powerpoint lecture notes for lesson 6
Powerpoint lecture notes for lesson 7
Overview of software requirements
Pentaho Data Integration installation
Overview of database software installation
Oracle installation notes
Making connections to a local Oracle database
Optional textbook reading material
Module 1 quiz

Multidimensional Data Representation and Manipulation
Data cube representation video lecture
Data cube operators video lecture
Overview of Microsoft MDX video lecture
Microsoft MDX statements video lecture
Overview of WebPivotTable video lecture
WebPivotTable software demonstration
Powerpoint lecture notes for lesson 1
Powerpoint lecture notes for lesson 2
Powerpoint lecture notes for lesson 3
Powerpoint lecture notes for lesson 4
Powerpoint lecture notes for lesson 5
WebPivotTable Tutorial
Optional textbook reading material
Module 2 quiz

Data Warehouse Design Practices and Methodologies
Relational database concepts for multidimensional data video lecture
Table design patterns video lecture
Summarizability patterns for dimension tables video lecture
Summarizability patterns for dimension-fact relationships video lecture
Mini case for data warehouse design video lecture
Data warehouse design methodologies video lecture
Powerpoint lecture notes for lesson 1
Powerpoint lecture notes for lesson 2
Powerpoint lecture notes for lesson 3
Powerpoint lecture notes for lesson 4
Mini Case Study and Solution
Powerpoint lecture notes for lesson 5
Powerpoint lecture notes for lesson 6
Practice problems for module 3
Optional textbook reading material
Module 3 quiz

Data Integration Concepts, Processes,and Techniques
Concepts of data integration processes video lecture
Change data concepts video lecture
Data cleaning tasks video lecture
Pattern matching with regular expressions video lecture
Matching and consolidation video lecture
Quasi identifiers and distance functions for entity matching video lecture
Powerpoint lecture notes for lesson 1
Powerpoint lecture notes for lesson 2
Powerpoint lecture notes for lesson 3
Powerpoint lecture notes for lesson 4
Powerpoint lecture notes for lesson 5
Powerpoint lecture notes for lesson 6
Optional reading material
Module 4 quiz

Architectures, Features, and Details of Data Integration Tools
Architectures and marketplace video lecture
Common features of data Integration tools video lecture
Talend Open Studio video lecture
Pentaho Data Integration video lecture
Software video demonstration for Pentaho Data Integration
Course conclusion video lecture
Powerpoint lecture notes for lesson 1
Powerpoint lecture notes for lesson 2
Powerpoint lecture notes for lesson 3
Powerpoint lecture notes for lesson 4
Optional reading material
Guided tutorial for Pentaho Data Integration
Documents for the module 5 assignment
Module 5 quiz
Quiz for module 5 assignment

Summary of User Reviews

Discover the principles of data warehouse design with this comprehensive course on Coursera. Students have praised the content and delivery of the course, which covers a range of topics including data modeling, ETL design, and data integration. One key aspect that many users thought was good is the practical nature of the course, which provides hands-on experience with real-world examples.

Pros from User Reviews

Practical approach with real-world examples
Comprehensive coverage of data warehouse design principles
Clear and engaging delivery by the instructor
Good pacing and structure of the course
Helpful resources and assignments to reinforce learning

Cons from User Reviews

Some users found the course material too basic
A few technical issues with the Coursera platform
Lack of interaction with the instructor and other students
Could benefit from more hands-on exercises
Not suitable for advanced learners looking for more in-depth coverage

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