Lecture 4: Building Dimensional Models.pptx
- 1. Lecture 4 Building Dimensional Models
- 2. 2 Steps in the designing Dimensional Models 1. Choose a business process. Selecting the subjects from the information packages for the first set of logical structures to be designed. 2. Choose the grain of the fact table. Determining the level of detail for the data in the data structures. 3. Choose dimensions. Choosing the business dimensions (such as product, market, time, etc.) to be included in the first set of structures and making sure that each particular data element in every business dimension is conformed to one another. 4. Choose the measured fact. Selecting the metrics or units of measurements (such as product sale units, dollar sales, dollar revenue, etc.) to be included in the first set of structures. 5. Choose duration of the database. Determining how far back in time you should go for historical data.
- 3. Information packages • When requirements cannot be fully determined, we need a new and innovative concept to gather and record the requirements. • Users tend to think in terms of business dimensions and analyze measurements along such business dimensions. • To determine the measurements and the relevant dimensions that must be captured and kept in the data warehouse. You come up with what is known as an information package for the specific subject.
- 4. • A new concept of acquiring business requirements • Are used in the business requirements definition phase • Information Package diagrams help to capture ; • critical metrics measuring the performance of the business units • The business dimensions along which the metrics are analyzed • The details of how drill-down and roll-up analyses are done Information packages
- 5. 5 Business Requirements phase essentially help to compile information packages for all the subjects of the Data Warehouse • Define the common subject areas • Design key business metrics • Decide how data must be presented • Determine how users will aggregate or roll up • Decide the data quantity for user analysis or query • Decide how data will be accessed • Establish data granularity • Estimate data warehouse size • Determine the frequency for data refreshing • Ascertain how information must be packaged Information packages
- 6. Information Package Diagram (Subject – Sales Analysis) Time Periods Locations Products Age Groups Year Country Class Group 1 Measured Facts: Forecast Sales, Budget Sales, Actual Sales Hierarchies Dimensions
- 7. 7 •Goal : To analyze sales. •User analysis: By product, Analysis by breaking the sales down by dealers. •As an automaker, you would want to know who is buying your automobiles and in what quantities. How do the customers pay for the automobiles? What effect does financing for the purchases have on the sales (method of payment)? Identify Subject, dimensions, facts (metrics) Example business cases – Automobile manufacturer
- 8. 8 Dimensions for the subject of sales for an automaker: 1. Product 2. Dealer 3. Customer 4. Method of payment 5. Time. Example business cases – Automobile manufacturer
- 9. 9 Hierarchies and categories are included in the information packages for each dimension. 1. Product: Model name, model year, product category, exterior color, interior color, first model year, engine capacity 2. Dealer: Dealer name, city, state, single brand flag, date first operation 3. Customer : Age, gender, income range, marital status, household size, vehicles owned, home value, own or rent 4. Payment method: Finance type, term in months, interest rate, agent 5. Time: Date, month, quarter, year, day of week, day of month, season, holiday flag Example business cases – Automobile manufacturer
- 10. 10 Key business metrics or facts Numbers about the sale of each individual automobile. 1. Actual sale price 2. Options price 3. Full price 4. Dealer add-ons 5. Dealer credits 6. Dealer invoice 7. Amount of down payment 8. Manufacturer proceeds 9. Amount financed Example business cases – Automobile manufacturer
- 11. Time Product Payment Method Customer Demographics Dealer Year Model Name Finance Type Age Dealer Name Quarter Model Year Term (Months) Gender City Month Package Styling Interest Rate Income Range State Date Product Line Agent Marital Status Single Brand Flag Day of week Product Category Household Size Date First Operation Day of Month Exterior Color Vehicles Owned Session Interior Color Home Value Holiday flag First Year Own or Rent Measured Facts: Actual Sale Price, MSRP Sale Price, Options Price, Full Price, Dealer Add-ons, Dealer Credits, Dealer Invoice, Down Payment, Proceeds, Finance Hierarchies Dimensions
- 12. 12 TIME PAYMENT METHOD PRODUCT CUSTOMER DEALER AUTO SALES Dimensional Model (Automaker sales)
- 13. 13 • The subject in this case is hotel occupancy. • User analysis: • occupancy of the rooms in the various branches of the hotel chain. • occupancy by individual hotels and by room types. Example business cases – Hotel Serena
- 14. 14 • In the hotel occupancy information package, the dimensions included are • hotel • room type • time. Example business cases – Hotel Serena
- 15. 15 Hierarchies and categories are included in the information packages for each dimension. 1. Hotel: Hotel line, branch name, branch code, region, address, city, state, Zip Code, manager, construction year, renovation year 2. Room type: Room type, room size, number of beds, type of bed, maximum occupants, suite, refrigerator, kitchenette 3. Time: Date, day of month, day of week, month, quarter, year, holiday flag Example business cases – Hotel Serena
- 16. 16 Key business metrics or facts Numbers about the occupancy of rooms. 1. Occupied rooms 2. Vacant rooms 3. Unavailable rooms 4. Revenue Example business cases – Hotel Serena
- 17. Information Package Diagram (Hotel Serena) Time Hotel Room type Year Hotel Line Room Type Quarter Branch Name Room Size Month Branch Code Number of Beds Date Region Type of Bed Day of week Address Max. Occupants Day of Month City/State/Zip Suite Session Construction Year Refrigerator Holiday flag Renovation Year Kitchen Measured Facts: Occupied Rooms, Vacant Rooms, Unavailable Rooms, Revenue Hierarchies Dimensions
- 18. 18 ORDER order_num (PK) customer_ID (FK) store_ID (FK) clerk_ID (FK) date STORE store_ID (PK) store_name address district floor_type CLERK clerk_id (PK) clerk_name clerk_grade PRODUCT SKU (PK) description brand category CUSTOMER customer_ID (PK) customer_name purchase_profile credit_profile address PROMOTION promotion_NUM (PK) promotion_name price_type ad_type ORDER-LINE order_num (PK) (FK) SKU (PK) (FK) promotion_key (FK) dollars_sold units_sold dollars_cost ERD
- 19. 19 TIME time_key (PK) SQL_date day_of_week month STORE store_key (PK) store_ID store_name address district floor_type CLERK clerk_key (PK) clerk_id clerk_name clerk_grade PRODUCT product_key (PK) SKU description brand category CUSTOMER customer_key (PK) customer_name purchase_profile credit_profile address PROMOTION promotion_key (PK) promotion_name price_type ad_type FACT time_key (FK) store_key (FK) clerk_key (FK) product_key (FK) customer_key (FK) promotion_key (FK) dollars_sold units_sold dollars_cost DIMENSONAL MODEL
Editor's Notes
- #10: what exactly are the users analyzing? What numbers are they analyzing? The numbers the users analyze are the measurements or metrics that measure the success of their departments. These are the facts that indicate to the users how their departments are doing in fulfilling their departmental objectives.
- #16: what exactly are the users analyzing? What numbers are they analyzing? The numbers the users analyze are the measurements or metrics that measure the success of their departments. These are the facts that indicate to the users how their departments are doing in fulfilling their departmental objectives.