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Bank File Statement

The data model encompasses information on financial transactions, transaction types, daily balances, vendor payments, and customer payments derived from the bank file statement dataset. It allows tracking transactions and account activities, categorizing transaction types for analysis, monitoring daily balances for cash flow management, summarizing vendor payments for cost efficiency, and analyzing customer payments for revenue forecasting and customer behavior insights.

Benefits of This Data Model​

  • Enhanced Transaction Analysis: The data model facilitates detailed categorization of transaction types, allowing for in-depth analysis and insights into financial activities.
  • Improved Cash Flow Management: By providing daily balance information, the model enables better tracking of cash flow trends over time, aiding in proactive financial decision-making.
  • Optimized Cost Efficiency: The ability to summarize vendor payments helps in identifying spending patterns and optimizing cost management strategies for improved efficiency.
  • Effective Revenue Forecasting: Analyzing customer payments within the data model supports revenue forecasting efforts, enabling better insights into customer behavior and financial performance.

Key Performance Indicators (KPIs)​

  • Number of Entries: The total count of entries in the bank file statement dataset.

Available Visualizations​

View NameDescription
Bank File StatementOffers an overview of financial transactions, balances, and account activities from bank files.
Total TransactionsDisplays the total number of transactions processed within a specified time period.
Transaction TypesCategorizes transactions based on type (e.g., deposits, withdrawals, transfers) for analysis.
Daily BalancesProvides daily account balances to track cash flow and financial health over time.
Vendor PaymentsSummarizes payments made to vendors, helping identify spending patterns and manage costs efficiently.
Customer PaymentsAnalyzes payments received from customers, assisting in forecasting revenue and customer behavior.