12 Best Data Warehousing Training Courses to Grow Your Skills
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A data warehouse is essential to any organization using data science. More than just a repository, a data warehouse integrates data from multiple sources, and in various formats, so that it can be used for data analytics, data science, machine learning (ML), and artificial intelligence (AI). Being a data warehousing specialist is lucrative—salaries average in six figures, according to salary.com—and there are thousands of data warehousing jobs available today.
If all that sounds exciting to you, then you might be wondering: how do I become a data warehouse specialist? Well, this list is a great place to start. Below, we’ll tell you all about the 12 best data warehousing training courses, and what makes them each great, so that you can pick the course that’s right for you.
How Important Is Data Warehousing Training?
If you want to work with data, then you need to understand how data is stored, so data warehouse training is absolutely essential. Even if you aren’t working towards a data warehousing specialist position, it’s still important to understand the basics so that you can collaborate with the rest of your team.
12 Best Data Warehousing Training Courses
Here are the 12 best data warehousing training courses:
|Data Science Career Track||4.64||$9,900||Learn More|
|Data Warehousing for Business Intelligence Specialization||4.5||$49||Learn More|
|IBM Data Warehouse Engineer Professional Certificate||4.7||$39||Learn More|
|Data Warehouse – The Ultimate Guide||4.6||$99.99||Learn More|
|Data Warehouse Beginner||N/A||$19||Learn More|
|Data Warehouse Fundamentals for Beginners||4.5||$44.99||Learn More|
|BI Foundations with SQL, ETL and Data Warehousing Specialization||4.6||$39||Learn More|
|Data Warehousing and BI Certification Training||4.6||$296||Learn More|
|Modern Data Warehouse Platforms and Architectures||N/A||$299||Learn More|
|Data Warehousing on AWS||4.3||$2025||Learn More|
|Enterprise Data Management||4.0||$499||Learn More|
|Modeling Data Warehouse with Data Vault 2.0||4.4||$69.99||Learn More|
Springboard’s Data Science Career Track gives you a comprehensive foundation that’s needed to kickstart your career in data. It covers the skills and technologies employers look for, including Python programming, Matplotlib, and Seaborn, data wrangling, statistical inference, machine learning, programming, and advanced machine learning.
In this program, you will complete 14 mini-projects, multiple capstones, and an advanced specialization project, which you can add to your portfolio. The course includes 1-on-1 mentorship, career coaching, and a money-back job guarantee.
This program requires six months of active coding experience with a general-purpose language such as Python, R, Java, or C++. You are also expected to be comfortable with basic statistics, including probability, mean and median, standard deviation, distributions, and histograms.
Get To Know Other Data Science Students
It is a six-months program demanding a commitment of 15-20 hours per week. However, it is self-paced, and you can complete it in your own time.
When paid upfront, this course costs $9,900. You can also pay in monthly installments or choose the deferred tuition plan that begins after you start a data science job.
- Coursera: 4.5
This Coursera course is comprised of five courses concerning database management, data warehousing, and business intelligence. Offered by the University of Colorado, this program is designed to give learners an in-depth understanding of data warehousing, visualization, and analytics. The curriculum includes data modeling, SQL programming, data manipulation, data architecture, and warehouse design. You will work with tools such as MicroStrategy, OLAP (online analytical processing), and Visual Insights. At the end of the program, you’ll complete a capstone project in designing and building a data warehouse for business intelligence.
This is an advanced-level program designed for those familiar with cloud and data technologies.
This program can be completed at the suggested pace of six hours a week in eight months. However, it is self-paced, and you are welcome to complete it sooner.
You can audit all the material for free on Coursera. If you need a certificate, the monthly subscription costs $49.
- Coursera: 4.7
This professional certification is designed to prepare learners for an entry-level position in business intelligence or data warehousing engineering. It covers key topics such as creating data pipelines, querying data using SQL, and managing an enterprise data warehouse. You will work with tools and programming languages such as SQL, MySQL, PostgreSQL, DB2, Apache, Airflow, Kafka, and Cognos Analytics. It also includes several hands-on projects.
This is a beginner-friendly course, and no experience is necessary.
8 months, at 4 hours per week
You can audit all the material for free on Coursera. If you need a certificate, the monthly subscription starts at $39.
- Udemy: 4.6
This online course by Nikolai Schuler aims to help learners master data warehousing, dimensional modeling, and ETL processes. It covers skills in data architecture, warehouse design, infrastructure, ELT vs. ETL, columnar storage, OLAP Cubes, in-memory databases, massively parallel processing, and indexes. The course includes nine hours of video and offers a certificate of completion.
This is a beginner-friendly program, but having basic SQL skills is useful.
This Skillsoft program is designed to help learners build their foundations in data warehousing and the approaches to implementing it. The course teaches data warehouse architecture, implementation, schemas, processes, and reports. It also introduces you to RDBMS and data lakes, and Azure and AWS to give you a look into various technologies and products available.
This is a beginner-friendly course.
The curriculum includes two courses with video lectures lasting 2h 44m, and five books estimated to be read over 38h 25m.
To take this course, you need a Skillsoft membership that starts from $19 a month. Team plans and enterprise billing is also available.
- Udemy: 4.5
In this program, Alan Simons helps master data warehousing. The curriculum covers building a data warehouse, comparing data lakes and virtualization, evaluating architectural options, performing dimensional data modeling, and unifying and loading data for business intelligence purposes. Each module has a scenario-based quiz or practical assignments emphasizing the learning objectives.
Business analysts, data engineers, or database designers with/without experience in data warehousing.
The course includes five hours of on-demand video, which you can watch at your own pace.
- Coursera: 4.6
This program on Coursera is aimed to give learners the foundational skills for a career in data engineering, data management, business intelligence, or analytics. The specialization comprises four courses covering the basics of SQL, Linux commands, shell scripts, building and automating ETL/ELT, data pipelines, data lakes, data marts, and warehouses. Each course includes several hands-on assignments with several business intelligence tools as well as a class project that you can add to your portfolio.
This is a beginner-friendly program with no prior experience required.
This program can be completed in five months at the suggested pace of four hours per week.
You can audit all the material for free on Coursera. If you want a certificate, however, the monthly subscription starts at $39.
The data warehousing and BI certification training from Edureka aim to give learners expert knowledge in these fields, covering a comprehensive range of topics. During the course, you will also be working on various hands-on projects.
The curriculum includes:
- Data warehouse architecture, including relational vs. analytical databases, OLTP, OLAP, OLAP categories, data marts, ETL extraction, and transformation
- Dimensions tables
- Data modeling, including data normalization and dimensional modeling
- Building data warehouses with ERWin
- Projects with Talend DI
- Data visualization with Tableau
This is an intermediate-level program best for data warehousing specialists, analytics managers, data modelers, ETL developers, and BI developers.
The program lasts five weeks, with classes twice a week for three hours a day.
This program costs $296.
This course is a primer on data warehousing for the cloud. It covers platform architecture and scalability, trade-offs of performance and cost, workload requirements, and ML and analytics inside the data warehouse. It also introduces learners to cloud solutions such as AWS Redshift, Azure SQL Data Warehouse, Cloudera Data Warehouse, Google BigQuery, Oracle ADW, Snowflake, Teradata, and Yellowbrick.
This advanced course is best for those with experience in big data and cloud technologies.
The course lasts about 3-4 hours.
This program costs $299.
- Indeed: 4.3
This program focusing on Amazon Redshift helps learners gain skills and understand best practices in building data warehouses using the tool. It also demonstrates data warehousing using other AWS services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon Simple Storage Service (Amazon S3).
To successfully complete this program, you must be familiar with relational databases and database design concepts, so the course is best suited for those with data analytics or database management experience.
It is a 3-day program, with virtual or live sessions between 9 am and 6 pm.
- Niche: 4
This EdX course focuses on data management for enabling business intelligence. It covers transactional, raw/external datasets, data lakes, data strategy, data governance, relational databases/SQL, data integration, master data management, and big data technologies. You will also learn to visualize data using graphical marks and data stories.
This advanced-level program needs some familiarity with data technologies and software engineering.
This program is spread over 12 weeks, lasting 8-10 hours per week.
You can access the learning material through the audit track for free. To get a verified certificate, you need to upgrade for $499.
- Udemy: 4.4
This program on Udemy uses Data Vault 2.0 to teach the fundamentals of data warehousing, agile methodology, and big data. In this course, you will learn data vault architecture, advanced data modeling, dimensional models, integrations, and data vault design. The curriculum includes six hours of video lectures and seven additional resources.
This is an intermediate-level course best for someone familiar with databases, RDBMS, and SQL programming.
The lectures are six hours long, but you can complete the course at your own pace.
The course costs $69.99.
How Do You Choose a Data Warehousing Training?
As you can see from the variety of courses above, you can learn data warehousing anywhere between 3-4 hours to six months. Naturally, the depth of learning and confidence in your skills will come from investing time and practice. Depending on your career goals and current skill level, here are some factors to consider while choosing the right data warehouse training for you.
Data warehousing is a vast field with several cross-functional areas coming together. It covers the spectrum of data analysis, data science, cloud technologies, big data, ML, AI, software engineering, and more. A good training program will give you the foundation in processes, methodologies, best practices, and data warehouse solutions, all of which will enable you to learn more complex concepts independently.
Expertise of Instructors
Data technologies are rapidly evolving. They also overlap with several other cloud, software engineering, and security technologies. To gain career-ready skills, you need an instructor with experience implementing large data warehousing projects for reputable organizations. Evaluate some of their free training or talks to ensure you are comfortable with their teaching methods.
Reviews and Ratings
Most online programs have student ratings. Choose a program that’s highly rated by learners. Also, carefully read the reviews to understand if the course will meet your needs.
While evaluating pricing, focus on return on investment. Some courses may cost less than $20. However, the certificate from it, or the skills you’ve gained, might not have value in the job market. Choose a program that is more likely to give you the career transition you seek. Then, look for discounts, deferred payment plans, and scholarships to address affordability.
Every course, however long or short, demands a certain level of undivided attention from you. Before you sign up for a course, understand how much time commitment it needs. Schedule that into your calendar to ensure you can sustainably dedicate your time throughout the course.
Projects and Practical Experience
Video lessons are great for acquiring theoretical knowledge. But, you will gain real-world experience, face challenges, and learn decision-making skills only when you complete hands-on projects. Make sure that the data warehousing training you choose has a healthy mix of theory and practice.
Employers are more likely to trust candidates with verified certifications. Especially in specific technologies such as Google Cloud, AWS, and Oracle Cloud, accreditation from these organizations can add credibility to your skills. While choosing the right program, ensure that the certificate demonstrates your capabilities.
If career transition is your goal, you need a program that offers you all the resources you need, such as support with building your career strategy, making your resume/portfolio/LinkedIn profile, interview coaching, and negotiation training. Also, check if the program has a job guarantee.
Related Read: Data Science Interview Questions
Making the Most Out of Your Data Warehousing Course
Ask yourself these questions to make the most of your course:
How Will the Course Work?
A typical online course combines video lectures, reading resources, and practical assignments. Some programs, like the Springboard Data Science Career Track, also include weekly 1-on-1 sessions with your mentors and ongoing career coaching. Some programs might have live video lectures each week, while others might have pre-recorded lessons released in stages. Most of them are self-paced, allowing you to learn at your comfort and catch up, even if you fall behind once in a while.
What Should You Expect to Learn During a Data Warehousing Course?
Data warehousing is a complex cross-functional field. A good course should give you foundational skills and the confidence to continue learning on your own. Some of the key concepts you need to know are:
- Relational and analytical databases
- Data warehouse architecture
- Data lakes vs. data warehouse vs. data marts
- Dimensional modeling and data normalization
- Data visualization
- Data governance
What Will Your Schedule Look Like?
Comprehensive data warehousing training demands 15-20 hours a week. You would schedule a course like this throughout the week—1-2 hours each weekday and 5-10 hours over the weekend. Several courses require only 5-6 hours a week, which you can schedule over weekends.
FAQs About Data Warehousing Training
We’ve got the answers to your most frequently asked questions:
Are There Any Common Prerequisites for a Data Warehousing Course?
For any data warehousing course, you will be expected to understand software engineering, big data, database management, and cloud technologies. Basic familiarity will often do, so you don’t need expert-level skills in any of these areas.
Related Read: 10 Best Database Management Courses & Trainings
How Long Will It Take To Learn Data Warehousing?
A strong foundation in data warehousing will take 5-6 weeks to gain. However, if you’re already a data professional, you might be able to learn much faster.
Is There Coding in Data Warehousing?
While there are several no-code data warehousing tools today, it is undoubtedly an advantage for data warehouse engineers to know how to code.
What Is the Difference Between a Data Warehouse and a Database?
A database stores the current data needed to perform specific tasks. A data warehouse stores current and historical data from multiple sources to enable analytics, machine learning, and artificial intelligence applications.
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