4.2.1.1 Grain Classification

Data Catalog in DFCS provides the grain classification. Each grain can have one or more entities. Grains represent the smallest, indivisible units of financial data that form the foundation for processing and analyzing entities. These grains ensure granular-level detail and traceability across various entities. Examples include entries such as Customer Account, which identifies individual customer financial details, and Customer Account Transactions, which record specific financial movements. Date serves as a temporal dimension for tracking transaction timelines, while Exchange Rates provide currency conversion details essential for multi-currency operations. General Ledger Data consolidates financial information at the account level for reporting and analysis, complemented by Management Ledger for managerial insights. Other granular elements, such as Group Insurance Policy Beneficiary and Group Insurance Summary, capture policy-specific details, while Policy Claim, Policy Claim Transaction, and Policy Commission Transactions detail insurance operations. Finally, Party Consent represents customer authorization for processing sensitive financial data. These grains collectively create a robust and detailed framework for accurate and transparent financial accounting.

Some of the examples for grain counts are Customer Accounts, General Ledger Data.