The Semantic Data Share: AI-Enabled Financial Analytics Powered by Snowflake Cortex

# **Overview**

The Dataplatr Financial Analytics Accelerator for Oracle Financials Accounts Payable is delivered as a Snowflake Data Share — a ready-to-consume, AI-ready analytical foundation built natively on the Snowflake Data Cloud. It bridges the gap between complex Oracle Financials AP data and actionable business intelligence through three high-fidelity semantic views: AP Invoice Aging, AP Invoice Distributions, and AP Invoice Aggregate.

Snowflake Semantic Views capture the metadata required for consistent and accurate AI-powered analytics, such as synonyms, sample values, and verified queries. These semantic views translate raw Oracle AP tables into structured, self-describing models that Snowflake Cortex Analyst can navigate using natural language — enabling finance and procurement teams to query vendor payment aging, invoice distribution spend, payment performance KPIs, and year-over-year AP trends without writing a single line of SQL.

The three semantic views each serve a distinct analytical purpose — point-in-time aging snapshots, granular distribution line detail, and pre-aggregated executive KPIs — providing complete AP coverage in a single, unified data share.

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# Business Use Cases

**Example 1 -** <br/>"Give me a breakdown of our total outstanding AP balance for the Feb-26 snapshot. I need to see the results grouped by Vendor Name and Age Bucket. Ensure you show the specific vendor names like Mastercard, Regions Bank, and Quora. At the end, provide two visuals: a bar chart showing balance by vendor and a pie chart showing the distribution across all aging buckets including 'Current', '31-60', '61-90', and '>120 Days'."

**Example 2 -** <br/>"Give me an operational overview of our AP aging for the current fiscal year 2026. Use the snapshot month to show the trend of the Total Outstanding Balance and the Invoice Count for each period. I want to understand if our overdue volume is growing or shrinking month-over-month. Conclude with a stacked bar chart showing the balance distribution for Jan, Feb, and March 2026, sliced by the Operating Unit Name so we can see which business units have the highest aging exposure."

**Example 3 -** <br/>"Show me the trend of our total outstanding AP balance month-over-month for the current fiscal year. Use the snapshot month for the comparison and include the total invoice count for each period. I want to see if our balance is increasing or decreasing as we move through 2026. Finish with a stacked bar visual comparing the outstanding balance for Jan, Feb, and March 2026."

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# **Why Choose the Dataplatr Financial Analytics Accelerator ?**

## **Finance-Aware Data Architecture**

The AP Invoicing Agent is built on a specialized foundation for complex Oracle Financials Accounts Payable logic. It delivers a high-fidelity schema that inherently reflects the logical relationships between AP Invoices, Distributions, Ledgers, Code Combinations, Supplier Sites, and Accounting Periods — ensuring the data is AI-ready for immediate use within the Snowflake ecosystem.

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## **Seamless Integration & Bespoke Customization**

Dataplatr specializes in customization these data assets to your specific Oracle Financials environment. We excel at extending the AP Invoicing Agent with external silos — such as Treasury, Procurement Contracts, or ERP Payment Runs — to create a unified, 360-degree Accounts Payable view. This schema can be customised by Dataplatr to align with your unique industry logic and payment reporting requirements.

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## **AI-First Design for Snowflake Cortex**

The AP Invoicing Agent provides the semantic clarity needed for Snowflake Cortex Analyst to accurately navigate Accounts Payable data. Our configuration-driven design allows for the addition of new dimensions or tables without heavy data engineering. Dataplatr can further extend this foundation to facilitate rapid expansion into Accounts Receivable, Cash Management, and Fixed Assets.

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## **End-to-End Financial Visibility**

The AP Invoicing Agent provides the clean, structured foundation required for a connected view of the Accounts Payable function. The architecture supports integration across General Ledger, Accounts Receivable, and Procurement — providing the audit-ready transparency necessary for enterprise-wide cash flow automation and financial control.

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## **The Dataplatr Advantage**

The Dataplatr Financial Analytics Accelerator provides a ready-to-deploy, AI-ready foundation on Snowflake. By combining ELT automation with Dataplatr's deep expertise in Oracle Financials customization, we help enterprises modernise AP workflows and achieve faster time-to-insight. Whether you are analysing vendor payment aging across operating units or benchmarking on-time payment rates quarter over quarter, Dataplatr ensures your AP data is clean, connected, and intelligent.

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