Question 1

What is a data warehouse, and why is it important to learn about?

Accepted Answer

A data warehouse is an organized collection of structured data that is used for applications such as reporting, analytics, or business intelligence. Traditional, on-premise data warehouses are still maintained by hospitals, universities, and large corporations, but these are expensive and space-consuming by today’s standards. Instead, data warehouse solutions like Google BigQuery and Amazon Redshift are allowing organizations of all sizes to benefit from the scalability and cost-effectiveness of cloud computing.

Data warehouses are important to learn about because they enable organizations to make data-driven decisions that can inform daily operations as well as future strategic initiatives. Analysts can use the data integration and extraction, transformation, loading (ETL) capabilities of business intelligence software like Pentaho to query and present information visually for maximum impact.

Working with diverse big data sets may require the use of a data lake, which is similar to a data warehouse but can take in all types of data - structured, unstructured, and raw. With software like Apache Hive, data scientists can sort and analyze data delivered by data lake solutions like Amazon S3 and Microsoft Azure to generate the real-time and predictive insights big data can provide.

Question 2

What kinds of careers can I have with a background in data warehousing?

Accepted Answer

An organization’s data warehouse is one of its most valuable assets, and it is important for personnel across a wide variety of departments to understand how to access it and how to leverage its data effectively. For example, quantitative financial analysts may use data warehouses to feed machine learning algorithms for stock trading; digital marketing experts rely on detailed datasets on consumer buying behavior; and supply chain managers analyze operational data to guide process improvements.

Data engineers are the primary personnel responsible for the design and maintenance of the data infrastructure of an organization, including not only data warehouses but data pipelines, data lakes, and databases. They must be familiar with programming languages and frameworks like Python, SQL, and Java, and usually have at least a bachelor’s degree or even a master’s degree in computer engineering or computer science. The national average salary for a data engineer according to Glassdoor is $103,864 per year.

Question 3

Can I learn about data warehousing by taking online courses on Coursera?

Accepted Answer

Yes - in fact, data science topics like data warehousing are some of the most popular online learning opportunities on Coursera. There are a wide variety of online courses and Specializations available on data warehousing, as well as related courses on data engineering, database management, and business intelligence. And you can take courses from top-ranked institutions and industry leaders, including the University of Colorado, the University of California Davis, and Google Cloud, so you don’t have to sacrifice the quality of your education for the opportunity to learn online.

Question 4

What skills or experience do I need to already have, before starting to learn data warehouse?

Accepted Answer

Before starting to learn about data warehouse concepts, it’s extremely important to already have strong computer programming skills, a data architecture background, and insights in working with teams of developers, systems architects, and other high-level developers. Designers of data warehouses tend to have computer science degrees and fundamental knowledge of data integration processes. These skills are crucial to working in this field, as businesses rely heavily on data and analytics to stay competitive. Data moves from transaction systems and company databases into warehouses. This data is then extracted into company reports, dashboards, and analytics tools to help guide their decision-making. Having strong experience in data architectures and company operations will be a well-guided step to learning the business of data warehouse.

Question 5

What kind of people are best suited for roles in data warehouse?

Accepted Answer

Clearly, business analysts, data engineers, and data scientists are all best suited for work that involves data warehousing. Computer programmers are often at the foundation in a data warehouse, using their programming skills and analytical thinking to extract the data. Once extracted, results are usually presented in the top tier via a front-end client through reporting, analysis, and data mining tools. An analytics engine exists in the middle tier to access and analyze the data. And finally, data is loaded and stored in the database server, in the bottom tier of the architecture. These data professionals working in a data warehouse can then present their findings to senior company leaders through reports, charts, and spreadsheets, to help them make important decisions.

Question 6

How do I know if learning data warehouse is right for me?

Accepted Answer

Learning about data warehouse work might be a great fit for you if you are organized, have a computer software design background, and may even be already working in a data engineer type role or aspiring to work somehow with big data and cloud serving technology. These aspects are all crucial to data warehouse work, which is focused on extracting data from real-world transactional behavior. For instance, a data warehouse may combine customer information from a company's POS system, its email lists, and its physical mailing lists into one large database. If you are the sort of person who is passionate about learning about business intelligence tools and how a data warehouse can coordinate this data for you, then learning data warehouse information may certainly be a great path ahead.

Question 7

What are the benefits of taking an online Data Warehouse course?

Accepted Answer

Online Data Warehouse courses offer a convenient and flexible way to enhance your knowledge or learn new Data Warehouse skills. Choose from a wide range of Data Warehouse courses offered by top universities and industry leaders tailored to various skill levels.

Question 8

What Data Warehouse courses are best for training and upskilling employees or the workforce?

Accepted Answer

When looking to enhance your workforce's skills in Data Warehouse, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.

Data Warehouse Courses Online

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Explore the Data Warehouse Course Catalog

Data Warehouse Fundamentals

IBM Data Warehouse Engineer

Data Warehouse Concepts, Design, and Data Integration

Data Warehousing: Schema, ETL, Optimal Performance

Data Warehousing for Business Intelligence

Modern Data Warehouse Analytics in Microsoft Azure

What brings you to Coursera today?

BI Foundations with SQL, ETL and Data Warehousing

Python for Data Science, AI & Development

Introduction to Data Analytics

Databases and SQL for Data Science with Python

IBM Data Engineering

The Path to Insights: Data Models and Pipelines

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Frequently Asked Questions about Data Warehouse

What is a data warehouse, and why is it important to learn about?‎

What kinds of careers can I have with a background in data warehousing?‎

Can I learn about data warehousing by taking online courses on Coursera?‎

What skills or experience do I need to already have, before starting to learn data warehouse?‎

What kind of people are best suited for roles in data warehouse?‎

How do I know if learning data warehouse is right for me?‎

What are the benefits of taking an online Data Warehouse course?‎

What Data Warehouse courses are best for training and upskilling employees or the workforce?‎

Other topics to explore