Purpose General Ledger Period Budget Use Case Owner: Soon TanTypical Use Case: General Ledger Period BudgetStyle: Fact Source Key Parameters CompanyLedger_ID (Created)PRUProject_IDAccount_ID Sample Exec Response SEQ Dates Measures Codes SQL
Purpose General ledger Transaction Use Case Owner: Soon TanTypical Use Case: General ledger TransactionStyle: Fact Source Key Parameters CompanyLedger_ID (Created)PRUProject_IDAccount_ID Sample Exec Response SEQ Dates Measures Codes SQL
Purpose General Ledger Project Balance Use Case Owner: Soon TanTypical Use Case: General Ledger Project BalanceStyle: Fact Source Key Parameters CompanyLedger_ID (Created)PRUProject_IDAccount_ID Sample Exec Response SEQ Dates Measures Codes SQL
Purpose General Ledger Balance Set Use Case Owner: Soon TanTypical Use Case: General Ledger Balance SetStyle: Fact Source Key Parameters CompanyLedger_ID (Created)PRUProject_IDAccount_ID Sample Exec Response SEQ Dates Measures Codes SQL
Purpose Provides Fact Data Use Case Owner: Soon TanTypical Use Case: General Ledger BalanceStyle: Fact Source Key Parameters CompanyLedger_ID (Created)PRUProject_IDAccount_ID Sample Exec Response SEQ Dates Measures Codes SQL
Purpose Details Use Case Owner: Soon TanTypical Use Case: General LedgerStyle: Details Source Key Parameters CompanyLedger_ID (Created)Account_IDPRUPROJECT_ID Sample Exec Response SEQ Dates Codes SQL
Purpose Provides Management Account Structure Use Case Owner: Soon TanTypical Use Case: Financial Account StructureStyle: Detail Source Key Parameters CompanyAccount Code Sample Exec Response Level 1 Heading Grouping 1 Grouping 2 Leaf Account SQL
Set a goal to achieve zero downtime for data systems. This would involve building robust redundancy, fail-over mechanisms, and automated recovery processes to ensure continuous data availability.
Strive to make data accessible to everyone in the organisation, regardless of technical expertise. Implement self-service analytics tools, intuitive dashboards, and comprehensive data documentation to empower all stakeholders to make data-driven decisions.
Set a goal to build a data processing pipeline that can effortlessly handle massive volumes of data without any performance degradation. This could involve leveraging technologies like Apache Spark, Apache Flink, or Google Dataflow to achieve seamless scalability.