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I am doing a simple database design task as a training exercise where I have to come up with a basic schema design for the following case:

I have a parent-child hierarchy of products (example, Raw Material > Work in Progress > End Product).

  • Orders are placed at each level.
  • Number of orders shall be viewable in weekly buckets for the next 6 months.
  • Demand forecast can be done for each product level.
  • Demand forecast for any week within next 6 months can be done today.
  • Demand forecast is done for weekly buckets, for the next 6 months.

Demand Forecast is usually done at the higher level in hierarchy (Raw Material or Work in Progress level) It has to be disaggregated to a lower level (End Product).

There are 2 ways in which demand forecast can be disaggregated from a higher level to lower level:

  1. User specifies percentage distribution for end product. Say, there's a forecast of 1000 for Work In Progress.. and user says I want 40% for End Product 1 and 60% for End Product 2 in bucket 10.. Then for 10th week (Sunday to Saturday) from now, forecast value for End Product 1 would be 400 and, for End Product 2 would be 600.
  2. User says, just disaggregate according to orders placed against end products in Bucket 5, and orders in bucket 5 for End Product 1 and 2 are 200 and 800 respectively, then forecast value for EP1 would be ((200/1000) * 100)% and for EP2 would be ((800/1000) * 100)% of forecast for 'Work in Progress'.

Forecast shall be viewable in weekly buckets for the next 6 months and the ideal format should be:

product name | bucket number | week start date | week end date | forecast value | created_on

PRODUCT_HIERARCHY table could look like this:

id  |   name                |   parent_id
__________________________________________
1   |   raw material        |   (null)
2   |   work in progress    |   1
3   |   end product 1       |   2
4   |   end product 2       |   2

ORDERS table might look like this:

id | prod_id | order_date | delivery_date | delivered_date

where,

prod_id is foreign key that references id of PRODUCT_HIERARCHY table,

How to store forecast? What would be a good basic schema for such a requirement?


My idea to select orders for 26 weekly buckets is:

SELECT
    COUNT(*) TOTAL_ORDERS,
    WIDTH_BUCKET(
        delivery_date,
        SYSDATE,
        ADD_MONTHS(sysdate, 6), 
        TO_NUMBER( TO_CHAR(SYSDATE,'DD-MON-YYYY') - TO_CHAR(ADD_MONTHS(sysdate, 6),'DD-MON-YYYY') ) / 7
    ) BUCKET_NO
FROM
    orders_table
WHERE
    delivery_date BETWEEN SYSDATE AND ADD_MONTHS(sysdate, 6);

But this will give weekly buckets starting from today irrespective of the day. How can I convert them to Sunday to Saturday weeks in Oracle?

Please help designing this database structure.

(will be using Oracle 11g)

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1  
sounds like you're building a data warehouse. order would be the fact table. product and date the dimension tables. You might want to use an accumulating fact table, as you are looking at a process that has several steps. –  Neil McGuigan Feb 10 '13 at 20:25

1 Answer 1

Okay, so here's the data model I came up with.

PRODUCT -- to store product information and maintain parent-child hierarchy

id  NUMBER  "Primary Key Not Null"                  
level_code  VARCHAR2    Not Null                    
name    VARCHAR2    Not Null                    
description VARCHAR2                        
parent_id   NUMBER  Foreign Key references PRODUCT(id)                  

ORDERS -- to store orders for products

id  NUMBER  "Primary Key Not Null"                  
prod_id     NUMBER  "Foreign Key references PRODUCT(id) Not Null"                   
order_type  VARCHAR2    "Not Null Default 'Default'"
order_qty   NUMBER  Not Null
order_date  NUMBER  Foreign Key references DATE_INFO(date_key)
delivery_date   NUMBER  "Foreign Key references DATE_INFO(date_key)
Check delivery_date >= order_date"

FORECAST -- to store forecast value for products (store value for higher levels, store value for lower levels after disaggregation from a parent)

id  NUMBER  "Primary Key Not Null"
product_id  NUMBER  "Foreign Key references PRODUCT(id) Not Null"
forecast_value  NUMBER  Not Null
week    NUMBER  "Foreign Key references DATE_INFO(date_key) Not Null"                   

DISAGGREGATION_RULES -- to store which method was used for disaggregating a value from a higher level to lower level and how much percentage got distributed to lower level

id  NUMBER  "Primary Key Not Null"
parent_product_id   NUMBER  "Foreign Key id references PRODUCT(id) Not Null"
child_product_id    NUMBER  "Foreign Key id references PRODUCT(id) Not Null"
method  VARCHAR2    Not Null                    
from_week   NUMBER  "Foreign Key references DATE_INFO(date_key) Not Null"
to_week NUMBER  "Foreign Key references DATE_INFO(date_key) Not Null Check end_week >= start_week"
percent_distribution    NUMBER  Not Null                    

DATE_INFO -- date dimension, has information about start date (has to be Saturday) and end date corresponding to the week in which a particular date falls

date_key    NUMBER  "Primary Key
Not Null"                   
full_date   DATE    Not Null                    
week_begin_date DATE    Not Null                    
week_end_date   DATE    Not Null

As for the bucket number .. I am calculating week start date (date on Saturday, in my case) with the following function

CREATE OR REPLACE FUNCTION get_week_start_date(v_bucket_num IN NUMBER)
  RETURN DATE
IS
  week_start_date DATE;
BEGIN
  SELECT (TRUNC(SYSDATE+2, 'IW')-2) + ((v_bucket_num-1) * 7)
  INTO week_start_date FROM dual;
  RETURN week_start_date;
END;
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