A Journey to Data Architect ..

  Traditional Data Warehouse Concepts A  data warehouse  is any system that collates data from a wide range of sources within an organization. Data warehouses are used as centralized data repositories for analytical and reporting purposes. A traditional data warehouse is located on-site at your offices. You purchase the hardware, the server rooms and hire the staff to run it. They are also called on-premises, on-prem or (grammatically incorrect) on-premise data warehouses. Facts, Dimensions, and Measures The core building blocks of information in a data warehouse are facts, dimensions, and measures. A  fact  is the part of your data that indicates a specific occurrence or transaction. For example, if your business sells flowers, some facts you would see in your data warehouse are: Sold 30 roses in-store for $19.99 Ordered 500 new flower pots from China for $1500 Paid salary of cashier for this month $1000 Several numbers can describe each fact, and we call these numbers  measures . Som

Two pioneers of data warehousing named Bill Inmon and Ralph Kimball had different approaches to data warehouse design. Kimball Method: Build Data Marts for each line of Business with refine data and then Load to Data Warehouse. The Kimball data warehouse design uses a “ bottom-up ” approach. Inmon Method: Build Data warehouse with refined data and then build Data Marts for each line of Business/Subject area. This is known as a top-down approach to data warehousing Data Warehouse Architecture: Traditional vs. Cloud A  data warehouse  is an electronic system that gathers data from a wide range of sources within a company and uses the data to support management decision-making. Companies are increasingly moving towards cloud-based data warehouses instead of traditional on-premise systems. Cloud-based data warehouses differ from traditional warehouses in the following ways: There is no need to purchase physical hardware. It’s quicker and cheaper to set up and scale cloud data warehouses.