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.‎

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.‎

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.‎