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Conversational Analytics
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Conversational Analytics

    Prepare your data for import to hila

    hila’s Conversational Finance application provides a standard schema for you to ingest your data. However, you can also ingest data with custom schemas and an external database.

    • Standard hCF schema — prepare your data for ingestion according to the standard Conversational Finance schema, continue with the rest of this topic.
    • Custom schema — prepare your data for ingestion with a custom schema, see Supporting a new domain and new schema.
    • Custom schema from CSV or PARQUET files — prepare your data for ingestion with a custom schema from CSV or PARQUET files, see Ingest custom data from a file.
    • Ingest data from an external database — prepare your data for ingestion from a database, see Ingest data from an external database.

    Conversational Finance schema

    Preparing your data for Conversational Finance involves two steps:

    1. Prepare your data (customer task)
    2. Configure hila to ingest the data (Professional Services or client IT task)

    Prepare your data

    You need to prepare your data for Conversational Finance in the form of CSV or PARQUET files that you give to your Professional Services or client IT contact for the next step.

    To set up and populate Conversational Finance with pilot data for your organization, you need to prepare and provide the data in a standard format. You can do this by running a custom report in your financial system and exporting the data to a file with the expected columns and data. Or you can export data from your financial system in an Excel file and then transform this data to this standard format.

    The Conversational Finance data model consists of fact tables (journal and plan) and dimension tables. The following tables show the relationships between these fact and dimension tables:

    Data Model

    Fact tables

    The fact tables are:

    Journal fact table

    Journal table contains transaction data from your general ledger in a normalized format. The following columns are available in the journal table:

    Column Name Data Type Format Examples
    company_code varchar   AUS
    posting_date date YYYYMMDD 20230215
    fiscal_year varchar 2023 2023
    fiscal_period varchar ### 001
    account_number varchar   0050301000
    company_currency varchar   AUD
    company_amount numeric(38,2)   5936.32
    global_currency varchar   USD
    global_amount numeric(38,2)   5936.32
    department_number varchar   M001
    cost_center_number varchar   US10_ADM4
    profit_center_number varchar   YB800
    purchase_order_number varchar   0012000411
    invoice_number varchar   INV-SP03278-240609
    supplier_number varchar   4500000942
    material_number varchar   RM13
    sales_order_number varchar   0000002695
    customer_number varchar   EWM17-CU02
    product_number varchar   EWMS4-01
    channel_number varchar   CH001
    division_number varchar   DV0001
    transaction_type varchar   Purchase
    transaction_document_number varchar   BD2301000014
    transaction_document_item varchar   001
    transaction_description varchar    
    reference procedure varchar    
    transaction_id varchar    

    Comments:

    • Most of the columns are not required; however, the diversity of questions you can ask depends directly on the data being available in all or most of these columns.

    Plan fact table

    The plan table contains actual, budget, and forecast values at your desired aggregation level and combinations. Actual values may come from journal table or from other external sources. Budget and forecast values are expected to come from planning systems. The planning systems may also feed in actual values to plan table if these values are different from journal values. So the design supports “loose integration” of journal and plan tables. However, both journal and plan fact tables use the same dimension tables in the data model.

    Column Name Data Type Format Examples
    company_currency varchar   AUD
    company_actual_amount numeric(38,2)   5936.32
    company_budget_amount numeric(38,2)   6000.00
    company_forecast_amount numeric(38,2)   6200.00
    company_previous_forecast_amount numeric(38,2)   6100.00
    global_currency varchar   USD
    global_actual_amount numeric(38,2)   5936.32
    global_budget_amount numeric(38,2)   6000.00
    global_forecast_amount numeric(38,2)   6200.00
    global_previous_forecast_amount numeric(38,2)   6100.00
    company_code varchar   AUS
    fiscal_year varchar 2023 2023
    fiscal_period varchar   001
    profit_center_number varchar   YB800
    product_number varchar   INV-SP03278-240609

    Dimension tables

    The following dimension tables must be populated:

    Account table

    Account table contains general ledger account information. The following columns must be populated in this table for each of the accounts that appear in the journal table:

    Column Name Data Type Format Examples
    account_name varchar   COGS Direct Material
    account_type varchar   Expense
    account_type_code varchar   REV
    account_subtype varchar   Operating Expense
    account_subtype_code varchar   SAL_REV
    account_category varchar   Cost of Goods Sold
    account_number varchar   0050301000

    Comments:

    • account_type column is used to categorize accounts into different types like Revenue and Expense.
    • account_category column is used to categorize accounts into different categories like Cost of Goods Sold, Operating Expenses, etc.

    Channel table

    Provides details about the sales channels used by your organization. This table is optional, but it can help you analyze sales performance across different channels.

    Column Name Data Type Format Examples
    channel_name varchar   Online Store
    channel_number varchar   CH001

    Company table

    Company provides details about your company or companies.

    Column Name Data Type Format Examples
    company_name varchar   EverGreen Australia Pty Ltd
    company_country varchar   Australia
    company_region varchar   Oceania
    currency_code varchar   Oceania
    language_code varchar   en
    company_code varchar   AUS

    Cost center table

    Provides details about the cost centers in your organization. Use to track expenses and revenues for specific departments or functions within your organization.

    Column Name Data Type Format Examples
    cost_center_number varchar   CC1010
    cost_center_name varchar   Manufacturing Plant A

    Customer table

    Provides details about your customers. This table is optional, but it can help you analyze sales performance across different customer segments.

    Column Name Data Type Format Examples
    customer_number varchar   CS08001
    customer_name varchar   Acme Retailers

    Department table

    Provides details about the departments in your organization. Use to categorize costs and revenues for specific functions or areas within your organization.

    Column Name Data Type Format Examples
    department_name varchar   Research and Development
    department_number varchar   DP001

    Division table

    Provides details about the divisions in your organization. Use to categorize costs and revenues for specific business units or divisions within your organization.

    Column Name Data Type Format Examples
    division_name varchar   Beverage Division
    division_number varchar   DV0001

    Fiscal calendar table

    If your organization follows a fiscal year calendar that is aligned with a calendar year, then you just need to provide the start date of the fiscal year. For example, if your fiscal year starts on 1st January, the fiscal year and calendar year are expected to be identical. If your fiscal year starts on 1st of July for example, then Q1 of the fiscal year would be 1st July to 30th September, Q2 would be 1st October to 31st December, and so on. In such cases, Professional Services will be able to generate a fiscal calendar table for queries automatically. However, if your organization follows a non-standard fiscal year calendar, you will need to provide a fiscal_calendar.parquet file.

    Column Name Data Type Format Examples
    fiscal_year varchar 2023 2023
    fiscal_period varchar ### 001
    fiscal_quarter varchar Q# Q1
    fiscal_month varchar MM 01
    posting_date varchar YYYYMMDD 20230215

    Comments:

    • If your organization follows a fiscal year calendar that is aligned with a calendar year, then you just need to provide the start date of the fiscal year.

    Fiscal period table

    Provides details about the fiscal periods in your organization. This table is optional, but it can help you analyze financial data across different fiscal periods.

    Column Name Data Type Format Examples
    fiscal_quarter varchar Q# Q1
    fiscal_month varchar MM 01
    fiscal_year varchar 2023 2023
    fiscal_period varchar ### 001

    Material table

    Provides details about the materials used in your organization. This table is optional, but it can help you analyze costs and revenues associated with specific materials.

    Column Name Data Type Format Examples
    material_name varchar   Polyethylene
    material_group_number varchar   MG0010
    material_number varchar   M090001

    Material group table

    Provides details about the material groups in your organization. This table is optional, but it can help you analyze costs and revenues associated with specific material groups.

    Column Name Data Type Format Examples
    material_group_name varchar   Plastics
    material_group_number varchar   MG0010

    Product table

    Provides details about the products in your organization. This table is optional, but it can help you analyze costs and revenues associated with specific products.

    Column Name Data Type Format Examples
    product_name varchar   Organic Almond Milk
    product_group_number varchar   PG0008
    product_number varchar   P060001

    Product group table

    Provides details about the product groups in your organization. This table is optional, but it can help you analyze costs and revenues associated with specific product groups.

    Column Name Data Type Format Examples
    product_group_name varchar   Dairy alternatives
    product_group_number varchar   PG0008

    Profit center table

    Provides details about the profit centers in your organization. Use to categorize costs and revenues for specific business units or profit centers within your organization.

    Column Name Data Type Format Examples
    profit_center_name varchar   Beverage Division
    profit_center_number varchar   PC0001

    Supplier table

    Provides details about the suppliers in your organization. Use to track costs and revenues associated with specific suppliers.

    Column Name Data Type Format Examples
    supplier_name varchar   Acme Packaging Solutions
    supplier_number varchar   SP03001
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