Star schema

In Peliqan you can model your data as you like, for example by using the Star schema data model. Below is a simple example where we build one fact table and a few dimension tables, based on tables from a CRM called “Teamleader”. The below queries can be created as Views in the data warehouse, to make them visible by your BI tool. See Query Settings > Create as view. Or you can “Materialize” these queries into a physical table in the data warehouse, using Query Settings > Replicate. More info: Materialize & Replicate

Star schema diagram: fact table fct_deals linked to dimension tables dim_customer and dim_status

Dimension table “customer”: dim_customer

The source table is the table “companies”, created by the ELT pipeline:

SELECT
  id AS customer_id,
  name,
  address
FROM teamleader.companies

Dimension table “status”: dim_status

The source is column “status” from the table “deals”, created by the ELT pipeline:

SELECT
  ROW_NUMBER() OVER () AS status_id,  -- Create an ID for each status
  status
FROM (
  SELECT DISTINCT
    status
  FROM teamleader.deals
  ORDER BY
    status
) AS t

Fact table “deals”: fct_deals

The fact table is created based on the source table “deals” from the ELT pipeline, combined with the id’s from the dimension tables, which are added as FK:

SELECT
  d.id AS deal_id,
  d.title AS deal_title,
  d.estimated_value_amount,
  d.weighted_value_amount,
  d.company_id AS customer_id,       -- FK to dimension Customer
  s.status_id                        -- FK to dimension Status
FROM teamleader.deals AS d
LEFT JOIN dim_status AS s
  ON d.status = s.status

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Dimension table “customer”: dim_customer

Dimension table “status”: dim_status

Fact table “deals”: fct_deals

​Dimension table “customer”: dim_customer

​Dimension table “status”: dim_status

​Fact table “deals”: fct_deals

Dimension table “customer”: dim_customer

Dimension table “status”: dim_status

Fact table “deals”: fct_deals