table_summary.txt

## Table: `dim_agreement`

### Schema: `public`

### All Columns and their Descriptions:
- `agreement_id` (text): Unique identifier for the agreement. This is likely the primary key.
- `customer_id` (text):  Identifier for the customer associated with the agreement.  This is likely a foreign key referencing a customer table.
- `agreement_type` (text):  The type of agreement (e.g., Service Level Agreement, Sales Agreement).
- `agreement_name` (text):  The name or title of the agreement.
- `agreement_status` (text): The current status of the agreement (e.g., Active, Inactive, Expired).
- `description` (text):  A textual description of the agreement.
- `document_number` (text): The document number associated with the agreement.
- `statement_of_intent` (text):  Indicates whether a statement of intent is associated with the agreement.
- `version` (text): The version number of the agreement.
- `initial_date` (timestamp without time zone): The date the agreement was initially created.
- `agreement_period_start_date` (timestamp without time zone): The start date of the agreement period.
- `agreement_period_end_date` (timestamp without time zone): The end date of the agreement period.
- `completion_date_start_date` (timestamp without time zone): The start date of the completion date.
- `completion_date_end_date` (text): The end date of the completion date.
- `auto_renewal` (text): Indicates whether the agreement has auto-renewal enabled.
- `commitment_unit` (text): The unit for the commitment amount (e.g., USD, hours).
- `rating_type` (text): The type of rating associated with the agreement.
- `commitment_amount` (text): The committed amount associated with the agreement.
- `remaining_payment_cycle` (text): The remaining payment cycle.
- `termination_date` (text): The date the agreement was terminated.

### Relationships with Other Tables (Foreign Keys):
- `customer_id` (FK) references a `customer` table (likely `dim_customer` or similar) on the `customer_id` column. This links the agreement to a specific customer.

### Cardinality of Relationships:
- Relationship with `dim_customer` (or similar) is one-to-many. One customer can have multiple agreements.

### Common Use Cases/Example Queries:
- Describe all active agreements for a specific customer.
- Analyze agreements by type or status.
- Track agreement start and end dates.
- Example SQL Snippet: `SELECT * FROM dim_agreement WHERE customer_id = 'customer_id_value' AND agreement_status = 'Active';`

### Data Constraints and Business Rules:
- `agreement_id` is likely unique and a primary key.
- `agreement_status` might have a controlled vocabulary (e.g., Active, Inactive).
- Date fields should be validated for data integrity.
- Business rules may dictate agreement approval processes or renewal cycles.

### Data Update Frequency/Volatility:
- Data is likely updated when agreements are created, modified, or terminated.
- Update frequency would depend on the business processes.

### Potential Pitfalls/Things to Avoid When Querying:
- Ensure correct date ranges when filtering by agreement period or completion dates.
- Be aware of potential data quality issues in text fields.

### Important Notes/Considerations for Querying:
- Join with the `dim_customer` table to retrieve customer information.
- Consider indexing frequently queried columns (e.g., `customer_id`, `agreement_status`, `agreement_type`).

---

## Table: `dim_customer`

### Schema: `public`

### All Columns and their Descriptions:
-   `customer_id` (text):  Likely the primary identifier for a customer.  This is probably the primary key, although not explicitly stated.
-   `customer_name` (text): The name of the customer.
-   `customer_start_date` (timestamp without time zone): The date the customer record became active.
-   `customer_end_date` (timestamp without time zone): The date the customer record became inactive.
-   `customer_status` (text): The status of the customer (e.g., Active, Inactive).
-   `is_customer_active` (integer):  Indicates whether the customer is currently active (1 or 0).
-   `customer_status_reason` (text): Reason for the customer's status.
-   `market_segment` (text): The market segment the customer belongs to.
-   `customer_segment` (text): The customer segment the customer belongs to.
-   `is_individual_customer` (integer): Indicates whether the customer is an individual (1 or 0).
-   `organization_name` (text): The name of the organization, if the customer is an organization.
-   `trading_name` (text): The trading name of the customer.
-   `organization_type_id` (text): The ID of the organization type.
-   `is_head_office` (boolean): Indicates if the customer is a head office.
-   `is_legal_entity` (boolean): Indicates if the customer is a legal entity.
-   `organization_start_date` (timestamp without time zone): The date the organization record became active.
-   `organization_end_date` (timestamp without time zone): The date the organization record became inactive.
-   `birth_date` (timestamp without time zone): The birth date of the customer, if an individual.
-   `death_date` (timestamp without time zone): The death date of the customer, if an individual.
-   `country_of_birth` (text): The country of birth of the customer, if an individual.
-   `party_status` (text): The status of the party.
-   `title` (text): The title of the customer, if an individual.
-   `generation` (text): The generation of the customer, if an individual.
-   `preferred_given_name` (text): The preferred given name of the customer, if an individual.
-   `given_name` (text): The given name of the customer, if an individual.
-   `middle_name` (text): The middle name of the customer, if an individual.
-   `family_name` (text): The family name of the customer, if an individual.
-   `family_name_prefix` (text): The family name prefix of the customer, if an individual.
-   `formatted_name` (text): The formatted name of the customer.
-   `full_name` (text): The full name of the customer.
-   `legal_name` (text): The legal name of the customer.
-   `gender` (text): The gender of the customer, if an individual.
-   `location` (text): The location of the customer.
-   `marital_status` (text): The marital status of the customer, if an individual.
-   `nationality` (text): The nationality of the customer, if an individual.
-   `place_of_birth` (text): The place of birth of the customer, if an individual.
-   `juridical_info` (text): Juridical information of the customer.
-   `latitude` (text): The latitude of the customer's location.
-   `longitude` (text): The longitude of the customer's location.
-   `number_of_employees` (text): The number of employees for the customer, if an organization.
-   `tax_exempt` (text): Indicates if the customer is tax-exempt.
-   `dunning_level` (text): The dunning level for the customer.
-   `contact_verified` (text): Indicates if the contact information is verified.
-   `customer_number` (text): The customer number.
-   `communication_method` (text): The communication method for the customer.
-   `sales_agent_id` (text): The ID of the sales agent.  Likely a foreign key to a `sales_agent` table.
-   `account_manager_id` (text): The ID of the account manager. Likely a foreign key to an `account_manager` table.
-   `sales_partner_id` (text): The ID of the sales partner. Likely a foreign key to a `sales_partner` table.
-   `party_identifier` (text): The party identifier.
-   `customer_revision` (bigint): The customer revision number.
-   `party_revision` (bigint): The party revision number.

### Relationships with Other Tables (Foreign Keys):
-   Based on the column names, it is *highly likely* that the table has foreign keys to tables such as: `sales_agent`, `account_manager`, and `sales_partner`. Without the ability to see the foreign key constraints, this is an educated guess.

### Cardinality of Relationships:
-   Relationship with `sales_agent`, `account_manager`, and `sales_partner` is likely one-to-many. One sales agent/account manager/sales partner can be associated with multiple customers.

### Common Use Cases/Example Queries:
-   Describe common use cases:
    *   Reporting on customer demographics.
    *   Analyzing customer sales by segment.
    *   Tracking customer status and activity.
    *   Identifying customers by sales agent or account manager.
-   Example SQL Snippet:
    ```sql
    SELECT customer_name, market_segment, customer_status
    FROM dim_customer
    WHERE sales_agent_id = 'XYZ123';
    ```

### Data Constraints and Business Rules:
-   `customer_id` is likely the primary key and should be unique and not null.
-   `customer_start_date` should be before or equal to `customer_end_date`.
-   `is_customer_active` should reflect the status of the customer based on `customer_start_date`, `customer_end_date`, and `customer_status`.
-   Data quality checks should be in place to ensure the accuracy of demographic data (e.g., valid gender, valid countries).

### Data Update Frequency/Volatility:
-   The data is likely updated frequently as customer information changes.
-   The volatility of the data will vary depending on the specific attributes (e.g., contact information will be more volatile than birthdate).

### Potential Pitfalls/Things to Avoid When Querying:
-   Joining to other tables without properly understanding the relationships, especially the role of `sales_agent_id`, `account_manager_id`, and `sales_partner_id`.
-   Incorrectly filtering on date ranges.  Consider using `customer_start_date` and `customer_end_date` to filter for active customers.
-   Not considering the impact of customer status when analyzing customer data.

### Important Notes/Considerations for Querying:
-   Always check `is_customer_active` or `customer_status` when querying to ensure you are getting the correct set of customers.
-   Be mindful of the date ranges when analyzing customer data over time.
-   Use the appropriate join conditions when joining with other tables.
-   Consider the impact of null values in fields such as `birth_date`, `death_date`, etc.


---


## Table: `dim_product`

### Schema: `public`

### All Columns and their Descriptions:

*   **product\_id (text):** Likely the primary identifier for the product. It's a text field. It is likely the primary key, though I don't have FK information.
*   **customer\_id (text):** The identifier for the customer associated with the product. Foreign key to the `dim_customer` table (inferred, as I lack foreign key info).
*   **agreement\_id (text):**  An identifier for the agreement related to the product.  Foreign key to the `dim_agreement` table (inferred).
*   **agreement\_name (text):**  The name of the agreement related to the product.
*   **product\_offering\_id (text):**  An identifier for the product offering. Potentially a foreign key to a `dim_product_offering` table (inferred).
*   **product\_offering\_name (text):** The name of the product offering.
*   **product\_name (text):** The name of the product.
*   **place\_id (text):** An identifier related to the product's location or place. Foreign key to `dim_place` (inferred).
*   **product\_class (text):** Categorization of the product (e.g., service, hardware).
*   **product\_status (text):** The current status of the product (e.g., active, inactive).
*   **is\_product\_active (integer):** Indicates if the product is active (1) or not (0).
*   **is\_product\_suspended (integer):** Indicates if the product is suspended (1) or not (0).
*   **is\_product\_in\_active (integer):** Indicates if the product is inactive (1) or not (0).
*   **is\_bundle (boolean):** Indicates if the product is part of a bundle (true) or not (false).
*   **order\_date (timestamp without time zone):** The date the product was ordered.
*   **start\_date (timestamp without time zone):** The date the product service started.
*   **price\_type (text):** The type of pricing associated with the product (e.g., recurring, one-time).
*   **price\_type\_value (text):** The value associated with the price type.
*   **recurring\_charge\_period (text):**  The period for recurring charges (e.g., monthly, annually).
*   **tax\_rate (double precision):** The tax rate applied to the product.
*   **duty\_free\_amount (double precision):** The duty-free amount for the product.
*   **tax\_included\_amount (double precision):** The amount of tax included in the product price.
*   **add\_product\_order\_item\_id (text):** Identifier for adding a product to an order item.
*   **delete\_product\_order\_item\_id (text):** Identifier for deleting a product from an order item.
*   **sales\_agent\_id (text):** The identifier of the sales agent. Foreign key to `dim_sales_agent` (inferred).
*   **sales\_partner\_id (text):** The identifier of the sales partner. Foreign key to `dim_sales_partner` (inferred).
*   **commitment\_duration\_units (text):** The units for the commitment duration (e.g., months, years).
*   **commitment\_duration (double precision):** The duration of the commitment.
*   **commitment\_term\_name (text):** The name of the commitment term.
*   **commitment\_term\_type (text):** The type of commitment term.
*   **usage\_duration\_units (text):** The units for the usage duration.
*   **usage\_duration (double precision):** The duration of the product usage.
*   **usage\_term\_name (text):** The name of the usage term.
*   **usage\_term\_type (text):** The type of usage term.
*   **guarantee\_amount (text):** The amount of guarantee associated with the product.
*   **device\_type (text):** The type of device associated with the product.
*   **gl\_code (text):** General Ledger code associated with the product.
*   **infrastructure (text):** The infrastructure associated with the product.
*   **ip\_address (text):** The IP address associated with the product.
*   **mac\_address (text):** The MAC address associated with the product.
*   **oss\_code (text):** OSS code associated with the product.
*   **smart\_card\_serialnumber (text):** The serial number of the smart card associated with the product.
*   **sla (text):** Service Level Agreement associated with the product.
*   **spec\_type (text):** Specification type of the product.
*   **specsub\_type (text):** Specification subtype of the product.
*   **resource\_model (text):** The resource model associated with the product.
*   **rating\_type (text):** The type of rating associated with the product.
*   **postpaid\_type (text):** The postpaid type associated with the product.
*   **brand\_name (text):** The brand name of the product.
*   **tv\_infrastructure (text):** The TV infrastructure associated with the product.
*   **revision (bigint):** Revision number of the product.
*   **href (text):** Hypertext reference (URL) associated with the product.

### Relationships with Other Tables (Foreign Keys):

*   **customer\_id:** Foreign key referencing `dim_customer`.
*   **agreement\_id:** Foreign key referencing `dim_agreement`.
*   **product\_offering\_id:** Foreign key referencing `dim_product_offering`.
*   **place\_id:** Foreign key referencing `dim_place`.
*   **sales\_agent\_id:** Foreign key referencing `dim_sales_agent`.
*   **sales\_partner\_id:** Foreign key referencing `dim_sales_partner`.

### Cardinality of Relationships:

*   Relationship with `dim_customer` is likely one-to-many (one customer can have many products).
*   Relationship with `dim_agreement` is likely one-to-many (one agreement can have many products).
*   Relationship with `dim_product_offering` is likely one-to-many (one product offering can be associated with many products).
*   Relationship with `dim_place` is likely one-to-many (one place can have many products).
*   Relationship with `dim_sales_agent` is likely one-to-many (one sales agent can be associated with many products).
*   Relationship with `dim_sales_partner` is likely one-to-many (one sales partner can be associated with many products).

### Common Use Cases/Example Queries:

*   **Tracking Product Details:** Retrieving detailed information about a specific product.
    *   Example SQL Snippet: `SELECT * FROM dim_product WHERE product_id = 'your_product_id';`
*   **Customer Product Overview:**  Listing all products associated with a specific customer.
    *   Example SQL Snippet: `SELECT * FROM dim_product WHERE customer_id = 'your_customer_id';`
*   **Aggregating product counts:** Calculating the number of products per product offering.
    *   Example SQL Snippet: `SELECT product_offering_name, count(*) FROM dim_product GROUP BY product_offering_name;`

### Data Constraints and Business Rules:

*   `product_id` is likely unique and not null.
*   `is_product_active`, `is_product_suspended`, and `is_product_in_active` should be mutually exclusive (only one can be true at a time).
*   Date fields (order\_date, start\_date) should be consistent with business timelines.

### Data Update Frequency/Volatility:

*   Data is likely updated frequently, with changes reflecting product status, customer associations, and order information.

### Potential Pitfalls/Things to Avoid When Querying:

*   Ensure proper joins when querying across related tables (e.g., `dim_customer`, `dim_agreement`).
*   Be aware of product lifecycle (status) when filtering data.  Consider `is_product_active` and other status flags.
*   Performance can suffer if large datasets are queried without appropriate indexes.

### Important Notes/Considerations for Querying:

*   Always join to other dimension tables (e.g., `dim_customer`, `dim_agreement`) to get a complete view of the product's context.
*   Use appropriate date ranges when analyzing product activity over time.
*   Consider the business rules related to product states when building queries.

---


## Table: `dim_product_order_item`

### Schema: `public`

### All Columns and their Descriptions:

-   `product_order_item_id` (text): Unique identifier for a product order item. Likely the primary key.
-   `product_order_id` (text): Likely a foreign key referencing a table containing product order information (e.g., `dim_product_order`).
-   `customer_id` (text): Likely a foreign key referencing the `dim_customer` table.
-   `agreement_id` (text): Likely a foreign key referencing the `dim_agreement` table.
-   `agreement_name` (text): Name of the agreement.
-   `order_item_agreement_id` (text): Identifier for the order item agreement.
-   `order_item_agreement_name` (text): Name of the order item agreement.
-   `billing_account_id` (text): Identifier for the billing account.
-   `sales_channel` (text): The sales channel through which the order was placed.
-   `order_date` (timestamp without time zone): The date the order was placed.
-   `order_status` (type): The status of the order (list status type: ACKNOWLEDGED,ASSESSING,CANCELLATION,CANCELLED,COMPLETED,INPROGRESS).
-   `order_item_status` (text): The status of the order item.
-   `order_description` (text): Description of the order.
-   `order_revision` (bigint): The revision number of the order.
-   `order_class` (text): The class of the order.
-   `order_href` (text): Hyperlink related to the order.
-   `order_item_type` (text): The type of the order item (e.g., 'Product', 'Service').
-   `quantity` (bigint): The quantity of the product ordered.
-   `order_item_price_type` (text): The price type of the order item (e.g., 'Recurring', 'One-time').
-   `order_item_recurring_charge_period` (text): The recurring charge period if applicable.
-   `order_item_tax_rate` (double precision): The tax rate applied to the order item.
-   `order_item_duty_free_amount` (double precision): The duty-free amount of the order item.
-   `order_item_tax_included_amount` (double precision): The tax-included amount of the order item.
-   `order_item_action` (text): The action performed on the order item (e.g., 'Add', 'Update', 'Delete').

### Relationships with Other Tables (Foreign Keys):

-   `customer_id` (FK) references `dim_customer`: Links the order item to a specific customer.
-   `agreement_id` (FK) references `dim_agreement`: Links the order item to a specific agreement.
-   `product_order_id`(FK) references `dim_product`: links the order item to a specific product order.

### Cardinality of Relationships:

-   Relationship with `dim_customer` is one-to-many. One customer can have multiple order items.
-   Relationship with `dim_agreement` is one-to-many. One agreement can have multiple order items.
-   Relationship with `dim_product_order` is one-to-many. One product order can have multiple order items.

### Common Use Cases/Example Queries:

-   Track sales and revenue by customer, product, and agreement.
-   Analyze order item status and trends.
-   Calculate total revenue and taxes.
-   Example SQL Snippet: `SELECT sum(quantity * order_item_tax_included_amount) FROM dim_product_order_item WHERE customer_id = 'customer123';`

### Data Constraints and Business Rules:

-   `product_order_item_id` should be unique.
-   `order_date` should be a valid date.
-   `quantity` should be a non-negative number.
-   `order_item_tax_rate`, `order_item_duty_free_amount`, and `order_item_tax_included_amount` should be valid numeric values.

### Data Update Frequency/Volatility:

-   Data is likely updated frequently, reflecting new orders, order updates, and cancellations.

### Potential Pitfalls/Things to Avoid When Querying:

-   Ensure correct join conditions when joining with other tables.
-   Be mindful of the `order_item_status` to filter for relevant order items.
-   Consider time-based filtering using `order_date` for trend analysis.

### Important Notes/Considerations for Querying:

-   This table is central to understanding product order details.
-   Join with `dim_customer` and `dim_agreement` for customer and agreement details.