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Conversational Finance
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Conversational Finance

    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.

    • Standard schema — to prepare your data for ingestion according to the standard Conversational Finance schema, continue with the rest of this topic.
    • Custom schema — to prepare your data for ingestion with a custom schema, see Ingest custom data.

    Conversational Finance schema

    Preparing your data for Conversational Finance involves two steps:

    1. Prepare the 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 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 text   AUS
    posting_date date YYYYMMDD 20230215
    fiscal_year text 2023 2023
    fiscal_period text ### 001
    account_number text   0050301000
    company_currency text   AUD
    company_amount numeric(38,2)   5936.32
    global_currency text   USD
    global_amount numeric(38,2)   5936.32
    department_number text   M001
    cost_center_number text   US10_ADM4
    profit_center_number text   YB800
    purchase_order_number text   0012000411
    invoice_number text   INV-SP03278-240609
    supplier_number text   4500000942
    material_number text   RM13
    sales_order_number text   0000002695
    customer_number text   EWM17-CU02
    product_number text   EWMS4-01
    transaction_type text   Purchase
    transaction_document_number text   BD2301000014
    transaction_document_item text   001
    transaction_description text    
    reference procedure text    
    transaction_id text    

    Comments:

    • Most of the columns are not required; however, the diversity of questions you can ask is directly dependent on 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_code text   AUS
    plan_category text    
    fiscal_year text 2023 2023
    fiscal_period text   001
    plan_value text   0050301000
    company_currency text   AUD
    company_amount numeric(38,2)   5936.32
    global_currency text   USD
    global_amount numeric(38,2)   5936.32
    profit_center_number text   YB800
    customer_number text   0012000411
    product_number text   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 text   COGS Direct Material
    account_type text   Expense
    account_type_code text   REV
    account_subtype text   Operating Expense
    account_subtype_code text   SAL_REV
    account_category text   Cost of Goods Sold
    account_number text   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.

    Company table

    Company provides details about your company or companies.

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

    Config table

    Column Name Data Type Format Examples
    config_key text   latest_closed_period
    config_value text   2024-P09

    Cost center table

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

    Customer table

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

    Department table

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

    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 text 2023 2023
    fiscal_period text ### 001
    fiscal_quarter text Q# Q1
    fiscal_month text MM 01
    posting_date text 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

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

    Material table

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

    Material group table

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

    Product table

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

    Product group table

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

    Profit center table

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

    Supplier table

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

    Configure hila

    After you have prepared the data, send the files to your Professional Services or client IT contact. They will configure hila to ingest the data and set up Conversational Finance for your organization.

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