project 04 Warehouse and Reporting
Turn raw data into trusted reports. Clean business records, build a tested model and create repeatable reports.
business question Profile raw CRM/sales records, build Silver and Gold tables in the disposable lab, explore the fact table, and publish repeatable reporting logic. you deliver Clean dimensions and facts, quality checks and customer, product and monthly reports. Exported as a report with your checked SQL, result evidence and written findings. skills Data cleaning · Data modeling · Reporting scope 6 milestones · 6 tables · advanced Start the first milestone milestones
01 Bronze: inspect raw data before cleaningInspect incoming records before making cleaning decisions. 02 Silver: clean, map & deduplicateClean values, apply mappings and remove duplicate records. 03 Gold: dimensions, facts & quality gatesBuild dimensions and facts with checks for trustworthy data. 04 EDA: explore before telling the storyExplore distributions and relationships before reporting. 05 Monthly change & cumulative reportsMeasure monthly change and cumulative totals. 06 Customer & product reporting contractsProduce customer and product reports at a defined level of detail. data Northstar Retail · 6 tables
Fictional CRM/catalog/sales extracts and curated star-schema tables. Raw keys, dates, quantities, and sales need validation. One fact row is one sales line.
bronze_customers 4 columns · 7 rows raw_id text name text country text updated_at text C001 Alice USA 2025-01-01 C001 Alice Nguyen US 2025-01-05 C002 Ben GB 2025-01-02 C003 Cara UK 2025-01-03 C004 Dev IND 2025-01-04
bronze_products 4 columns · 4 rows raw_id text name text category text price text P01 Notebook Stationery 12 P02 Desk lamp Home 45 P03 Keyboard Tech 80 P04 Headphones Tech 120
bronze_sales 6 columns · 13 rows row_id integer · key customer_id text product_id text quantity text sales text order_date text 1 C001 P01 2 24 2025-01-01 2 C002 P03 1 80 2025-01-02 3 C001 P02 1 45 2025-01-15 4 C003 P04 2 240 2025-02-01 5 C004 P03 2 160 2025-02-05
dim_customer 4 columns · 5 rows customer_key integer · key customer_id text name text country text 1 C001 Alice Nguyen United States 2 C002 Ben United Kingdom 3 C003 Cara United Kingdom 4 C004 Dev India 5 C005 Elena Canada
dim_product 5 columns · 4 rows product_key integer · key product_id text name text category text price real 1 P01 Notebook Stationery 12 2 P02 Desk lamp Home 45 3 P03 Keyboard Tech 80 4 P04 Headphones Tech 120
fact_sales 6 columns · 9 rows sale_key integer · key customer_key integer product_key integer quantity integer sales real order_date text 1 1 1 2 24 2025-01-01 2 2 3 1 80 2025-01-02 3 1 2 1 45 2025-01-15 4 3 4 2 240 2025-02-01 5 4 3 2 160 2025-02-05