Adventure Works Database Crash Course

Explore light Adventure Works database with fewer tables and a sales focus. Bridge tables convert many-to-many relationships and link sales order header to detail via order ID and product ID.

Explore field descriptions for Adventure Works sales orders, including revision number, order date, due date, ship date, status codes, and the online order flag.

Explore real-life one-to-many relationships with Adventure Works data, examining sales order headers and their details. Learn how the bridge table simplifies many-to-many relationships and clarifies product and order IDs.

Explore rowguid column and how a unique non clusters constraint supports replication, enabling unique identifiers across restored backups in the Adventure Works database crash course.

Explore the Adventure Works database schema, focusing on the dbo logging tables, build version and database log, and PCA (primary key), FK (foreign key), and U (unique key) concepts.

Explore the human resources schema by examining the central employee table with business entity id keys, the bridge table employee department history, and related department, pay history, and shifts data.

Explore the person schema as a central table linking employees, customers, and vendors through a shared business entity, with emails, phones, passwords, and diverse address types.

Examine the production schema of the Adventure Works database, focusing on the central product table, bill of materials, categories and subcategories, price history, languages, and work orders.

Explore the purchasing schema with the vendor as the central table, linking business entities and stores. Review ship methods, purchase order headers and details, and product vendor data.

Explore the sales schema, from the sales order header and detail to customers, stores, and currencies, including special offers, tax rates, territories, and credit card data.

Understand how data warehouses enable analytics and business intelligence by integrating historical data from diverse sources through ETL, using fact and dimension tables, data cube, and star or snowflake schemas.

Learn normalization and its impact on database design, comparing read-optimized data warehouses with write-optimized OLTP systems, and explain how splitting large tables reduces redundancy through relationships.

Trace the origins of Adventure Works data from OLTP to the data warehouse. Learn how documentation, including Microsoft 2008 data warehouse references, clarifies structure amid outdated resources.

Analyze how a date key surrogate from the date table, stored as integers, enables fast reads and supports fiscal and calendar periods for order, due, and ship dates.

Explore how etl transfers oltp data into data warehouse tables to build the reseller data warehouse, tracing columns from the person phone, person address, sales store, and product lines.

Explore the DimProduct and FactInternetSales schema by inspecting the DimProduct table, multilingual descriptions from the ProductDescription and Culture tables, and normalization with the Production tables.

Rebuild the fact internet sales table by linking the sales order header and detail, tracing dates, territory keys, unit price, taxes, freight, and totals in a data warehouse.