Getting Started with Data Warehousing and BI Analytics from Coursera

Kickstart your Data Warehousing and Business Intelligence (BI) Analytics journey with this self-paced course. You will learn how to design, deploy, load, manage, and query data warehouses and data marts. You will also work with BI tools to analyze data in these repositories.

You will begin this course by understanding different kinds of analytics repositories including data marts, data warehouses, data lakes, data lakehouses, and data reservoirs, and their functions and uses. They are designed to enable rapid business decision making through accurate and flexible reporting and data analysis.

A data warehouse is one of the most fundamental business intelligence tools in use today, and one that successful Data Engineers must understand. In this course, you will learn to design, model and implement data warehouses and explore data-warehousing architectures such as Star and Snowflake schemas. You will also learn how to populate data warehouses using ETL and ELT processes, verify data, query data and how to use Cubes, Rollups, and materialized views/tables.

You will become familiar with different BI tools used by experts in the industry such as IBM Cognos Analytics, Tableau, and Microsoft PowerBI. You will also use a BI tool to create data visualizations and build interactive dashboards to gain insights from data.

The hands-on labs in this course will enable you to apply what you learn and gain a practical knowledge of Data Warehousing and BI Analytics. You will work with repositories like MySQL, PostgreSQL, and IBM Db2. You will also use BI tools like Cognos Analytics. At the end of this course, you will complete a project to demonstrate the skills you acquired in each module.

What's inside

Syllabus

Data Warehouses, Data Marts, and Data Lakes

Welcome to your first module! This module provides a gentle but thorough introduction to data warehouse systems, data lakes, and data marts. When you complete this module, you’ll be able to identify and compare data warehouse systems, data mart, and data lake architecture, and understand how organizations can benefit from each of these three data storage entities. Optionally, you’ll explore the workings of IBM Db2 data warehouse system architecture, view use cases, and understand the key capabilities and integrations available with IBM Db2 Warehouse. Then, you’ll learn about three types of data warehouse systems and popular data warehouse system vendors. You will be ready to help your organization assess new data warehouse system offerings when you know the five essential, critical criteria, including total cost of ownership, to evaluate before changing to a new data warehouse system.

Designing, Modeling and Implementing Data Warehouses

In this knowledge-packed module, you’ll explore general and reference enterprise data warehousing architecture. You’ll discover how data cubes relate to star schemas. Then you’ll learn how to slice, dice, drill up or down, roll up, and pivot relative to data cubes. Next, you will examine the capabilities of materialized views, their benefits, and how to apply them. You’ll learn how data organization using facts and dimensions and their related tables organizes information. Then, you will explore how to use normalization to create a snowflake schema as an extension of the star schema. You will learn about populating a data warehouse, incremental data updates, verifying data, querying data, interpreting an entity-relationship diagram for a star schema, creating a materialized view, and applying the CUBE and ROLLUP options. You’ll also discover how organizations can benefit by implementing staging.

Data Warehouse Analytics

In this module, you’ll fast-track your data analytics learning and gain hands-on data analytics experience using IBM Cognos Analytics. After registering with Cognos Analytics, you’ll explore the platform’s capabilities by creating visualizations, building a simple dashboard, and trying out its advanced features.

Final Assignment and Final Quiz

In this module, you’ll complete your final course project, which brings together concepts and practices you previously learned in the first three modules. In this final project, you will design and load data into a data warehouse using facts and dimension tables. Then you’ll write aggregation queries using CUBE and ROLLUP functions and create materialized query tables, known as a materialized view. You will complete your project by using IBM Cognos to create an analytics dashboard.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by Rav Ahuja and Ramesh Sannareddy, who are recognized for their work in data warehousing and business intelligence

Explores data warehouses, data marts, and data lakes, which are essential concepts in modern data management

Teaches data warehousing design, modeling, and implementation, which are core skills for data engineers

Covers data warehouse analytics using IBM Cognos Analytics, a popular BI tool

Offers hands-on labs and interactive materials to reinforce learning

Reviews summary

Well-received data warehousing course

According to students, this data warehousing course has largely positive reviews. Learners appreciate the hands-on labs and clear content. They also mention that the course provides useful knowledge for those new to data warehousing. However, some students mention that the course could be improved by providing more real-life examples and case studies.

Suitable for those new to data warehousing.

"Really great introduction to Data warehouses, applications and operations inside them."

"This is a good course and introduces useful practical skills."

"An OK quick introduction to data warehousing."

Well-organized and easy-to-understand materials.

"Great organization and content"

"best course ,with a ver clear outline"

"Nice Course you will learn a lot"

Interactive labs provide practical experience.

"The labs were designed to get hands on experience."

"Every course in this professional certification program designed such way that to get hands on real time project experience."

"Knowledge of SQL is quite essential to complete the final assignment. Practice labs will help as everything is described."

Could benefit from more real-life examples and case studies.

"A great course. it will be good if you can add more real life examples and case studies."

"The videos are not engaging."

"some value, this course needs an overhaul."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Getting Started with Data Warehousing and BI Analytics with these activities:

Review Relational Database Concepts

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A refresher on relational database concepts will prepare you for the data modeling concepts covered in M02

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Review your notes or a textbook on relational database concepts
Practice writing SQL queries to create and manipulate tables

Review STAR and Snowflake Models

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Reviewing the concepts of STAR and Snowflake models will help you understand how data is organized and structured in data warehouses, which is essential for designing and implementing effective data warehouses.

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Read the chapter on STAR and Snowflake Models in the course textbook.
Watch the video lecture on STAR and Snowflake Models.
Complete the practice exercises on STAR and Snowflake Models.

Data Warehousing Study Group

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Joining a study group will give you the opportunity to discuss course material with other students, ask questions, and get help with challenging concepts.

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Find a study group or start your own.
Meet regularly to discuss course material.
Work together on projects and assignments.

Ten other activities

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Attend a Virtual Study Group on Data Warehousing Concepts

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Peer engagement can help strengthen understanding of concepts and approaches in M01 and M03

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Find a study partner or group online or through your university
Schedule regular virtual meetings to discuss course content and work on assignments together

Solve Data Modeling Exercises

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This exercise will help you hone your ability to design effective data models, which is essential for data warehousing

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Find a set of data modeling exercises online or in a textbook
Work through the exercises, carefully considering the relationships between different entities

ETL and ELT Process Exercises

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Practicing ETL and ELT processes will help you develop the skills necessary to load data into a data warehouse efficiently and effectively.

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Download the sample data set provided in the course materials.
Use a data integration tool to create an ETL or ELT process to load the data into a data warehouse.
Verify that the data was loaded correctly by running queries against the data warehouse.

Design a Sample Data Warehouse for a Healthcare Organization

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Prior exposure to concepts covered in M01 will help orient you and build your understanding

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Identify the data sources and requirements for the healthcare organization
Design the data warehouse schema using a star or snowflake model
Populate the data warehouse with sample data
Develop queries to analyze the data in the data warehouse

Tableau Tutorial

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Completing a tutorial on Tableau will help you learn how to use this powerful tool to create data visualizations and dashboards, which are essential for analyzing data and gaining insights from it.

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Enroll in the free Tableau tutorial offered by Coursera.
Complete the tutorial modules and exercises.
Create a data visualization or dashboard using Tableau based on the data from the course.

Explore Data Visualization with Tableau

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This activity will solidify the use and application of one of the BI tools introduced in M02

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Create a Tableau account and download the software
Follow a tutorial on how to create a basic visualization in Tableau
Practice creating visualizations using different types of charts and graphs
Explore the advanced features of Tableau, such as calculated fields and parameters

Develop an Infographic on the Benefits of Data Warehousing

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Creating an infographic will help you synthesize your understanding of data warehousing benefits

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Research the benefits of data warehousing
Identify the key points you want to communicate
Design an infographic that visually represents your key points

Design and Implement a Data Warehouse

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Designing and implementing a data warehouse will give you hands-on experience with the entire data warehousing process, from data modeling to data loading to data analysis.

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Choose a business problem that you want to solve with a data warehouse.
Design the data warehouse schema.
Load data into the data warehouse.
Create data visualizations and dashboards to analyze the data.
Present your findings to stakeholders.

Develop a Data Warehousing Implementation Plan

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Creating a data warehousing implementation plan will apply your knowledge of data warehousing concepts and methodologies

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Define the scope and objectives of your data warehousing project
Identify the data sources and requirements for your data warehouse
Design the data warehouse schema and ETL process
Develop a plan for data governance and security

Contribute to a Data Warehousing Open Source Project

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Contributing to an open-source project will expose you to real-world data warehousing challenges and solutions

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Find an open-source data warehousing project that interests you
Review the project's documentation and codebase
Identify an area where you can contribute
Submit a pull request with your proposed changes

Career center

Learners who complete Getting Started with Data Warehousing and BI Analytics will develop knowledge and skills that may be useful to these careers:

Business Intelligence Analyst

Business Intelligence Analysts use data to make informed decisions. This course can help Business Intelligence Analysts better understand the design, implementation, and management of data warehouses. This can help them more effectively analyze data and make better decisions.

See salaries and explore the career path for Business Intelligence Analyst

Data Warehouse Engineer

Data Warehouse Engineers implement and manage data warehouses. The hands-on labs in this course can help students gain practical knowledge of Data Warehousing and BI Analytics, which may help them succeed in this role.

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Data Analyst

Data Analysts collect, analyze, and interpret data to identify trends and patterns. This course can help Data Analysts better understand the design and implementation of data warehouses, which can help them more effectively analyze data.

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Data Architect

Data Architects design and manage data systems. This course can help Data Architects better understand the design and implementation of data warehouses.

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Data Engineer

Data Engineers design, build, and maintain data pipelines. This course can help Data Engineers better understand the design and implementation of data warehouses.

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Data Integration Specialist

Data Integration Specialists design and implement data integration solutions. This course can help Data Integration Specialists better understand the design and implementation of data warehouses.

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Database Administrator

Database Administrators manage and maintain databases. This course can help Database Administrators better understand the design and implementation of data warehouses, which can help them more effectively manage databases.

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Information Architect

Information Architects design and manage information systems. This course can help Information Architects better understand the design and implementation of data warehouses.

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Enterprise Architect

Enterprise Architects design and manage enterprise-wide systems. This course can help Enterprise Architects better understand the design and implementation of data warehouses.

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Solution Architect

Solution Architects design and manage solutions for specific business problems. This course can help Solution Architects better understand the design and implementation of data warehouses.

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Data Scientist

Data Scientists leverage data to solve complex problems. The information learned in this course may help Data Scientists better understand how to store and manage data for analysis.

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Cloud Architect

Cloud Architects design and manage cloud-based systems. This course can help Cloud Architects better understand the design and implementation of data warehouses.

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Software Architect

Software Architects design and manage software systems. This course can help Software Architects better understand the design and implementation of data warehouses.

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ETL Developer

ETL (Extract, Transform, Load) Developers design, develop, and maintain ETL processes. The information learned in this course may help ETL Developers better understand the design and implementation of data warehouses.

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Data Warehouse Architect

Data Warehouse Architects design, build, and maintain data warehouses. The information learned in this course may help Data Warehouse Architects design better data warehouse systems, especially if they are unfamiliar with the technologies used in the course.

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