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Ramesh Sannareddy and Rav Ahuja

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.

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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.

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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.
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Traffic lights

Read about what's good
what should give you pause
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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

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Reviews summary

Foundation in data warehousing and bi

According to students, this course provides a solid foundation in data warehousing and BI analytics, making it an excellent starting point for beginners. Learners particularly praise the practical, hands-on labs using tools like IBM Db2 and Cognos Analytics, which allow for real-world application of concepts. The explanations of core concepts such as data warehousing architectures and schema designs are frequently highlighted as clear and easy to understand. While some learners found the pace slightly slow or the depth insufficient for advanced users, the majority agree it equips them with essential skills for a career in data engineering or business intelligence. The final project is also seen as a valuable way to consolidate learning.
Content remains up-to-date and valuable for current industry practices.
"Even with evolving tech, this course felt current and the concepts are still highly relevant."
"I took this recently and found the content to be very much applicable to modern data practices."
"It's good to see that the course material is keeping pace with industry standards."
Best suited for those new to data warehousing and BI analytics.
"As someone completely new to data warehousing, this course was exactly what I needed to get started."
"If you're a beginner, this course is perfect. It covers all the basics without being overwhelming."
"Learners with some prior IT background might find the pace a bit slow, as it's truly introductory."
Well-organized modules culminating in a valuable final project.
"The course structure flows logically, building knowledge step by step towards the final project."
"The final assignment was excellent for integrating all the concepts learned throughout the modules."
"I appreciated how each module built upon the last, making the learning process smooth and coherent."
Provides a clear and comprehensive introduction to core data warehousing principles.
"The course did a great job explaining star and snowflake schemas; it was very easy to grasp."
"I found the initial modules on data warehouses vs. data lakes to be very clear and set a good foundation."
"Concepts like CUBE and ROLLUP functions were explained well, making complex ideas accessible."
Offers valuable hands-on experience with industry tools.
"The hands-on labs are truly the strongest part of this course; I found them incredibly useful for understanding concepts."
"Working with IBM Cognos Analytics and Db2 in the labs really solidified my understanding of data warehousing."
"I appreciated the practical application of ETL processes and dashboard creation, it's very helpful for real-world scenarios."
Some topics could benefit from more advanced or in-depth coverage.
"I would have liked to see more advanced topics, perhaps a deeper dive into performance optimization."
"The course provides a good overview, but doesn't go deeply into every single aspect of data warehousing."
"For someone with prior experience, the pace might feel a little slow at times."

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
A refresher on relational database concepts will prepare you for the data modeling concepts covered in M02
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Show steps
  • Review your notes or a textbook on relational database concepts
  • Practice writing SQL queries to create and manipulate tables
Review STAR and Snowflake Models
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.
Show steps
  • 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
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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Show steps
  • 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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Show all 13 activities
Attend a Virtual Study Group on Data Warehousing Concepts
Peer engagement can help strengthen understanding of concepts and approaches in M01 and M03
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Show steps
  • 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
This exercise will help you hone your ability to design effective data models, which is essential for data warehousing
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Show steps
  • 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
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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Show steps
  • 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
Prior exposure to concepts covered in M01 will help orient you and build your understanding
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Show steps
  • 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
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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Show steps
  • 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
This activity will solidify the use and application of one of the BI tools introduced in M02
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Show steps
  • 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
Creating an infographic will help you synthesize your understanding of data warehousing benefits
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Show steps
  • 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
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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Show steps
  • 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
Creating a data warehousing implementation plan will apply your knowledge of data warehousing concepts and methodologies
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Show steps
  • 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
Contributing to an open-source project will expose you to real-world data warehousing challenges and solutions
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Show steps
  • 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.
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.
Data Architect
Data Architects design and manage data systems. This course can help Data Architects better understand the design and implementation of data warehouses.
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.
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.
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.
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.
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.
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.
Information Architect
Information Architects design and manage information systems. This course can help Information Architects better understand the design and implementation of data warehouses.
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.
Software Architect
Software Architects design and manage software systems. This course can help Software Architects better understand the design and implementation of data warehouses.
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.
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.
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.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Getting Started with Data Warehousing and BI Analytics.
Highly respected resource for dimensional modeling, which widely used technique in data warehousing. It provides a comprehensive guide to designing and implementing dimensional data warehouses, including best practices and case studies.
Provides a comprehensive guide to developing with IBM Cognos Analytics 11, covering topics such as data modeling, report design, and dashboarding.
Provides a comprehensive overview of business intelligence and data warehousing, covering topics such as data modeling, data integration, and data mining.
Provides a comprehensive reference for Oracle Database 12c, covering topics such as data warehousing, data mining, and performance tuning.
Provides a practical guide to designing effective information dashboards, covering topics such as dashboard design principles, visual perception, and data visualization techniques.
Provides a practical introduction to data analytics, covering topics such as data collection, data cleaning, and data visualization.
Provides a comprehensive guide to building and managing data warehouses using Oracle. It covers topics such as data modeling, data integration, and data analysis, and is suitable for both beginners and experienced practitioners.

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