Email for Non-Technical Stakeholders

Original Scope Deliverable: Short email explaining the results of the data processing pipeline to non-technical stakeholders, highlighting key metrics (e.g., number of records processed, errors encountered). Note: This is the core deliverable for Task 5. Extended communication templates are available in the appendix/ folder.

Subject

Financial data processing pipeline results — January 2026 month-end run

To

Business Stakeholders

From

Data Platform Team

Date

February 1, 2026

Hi Team,

Sharing the results from the latest run of the new financial data processing pipeline (CSV → validated Parquet) and what it means for reporting and compliance.

What This Pipeline Does:

This new automated pipeline validates transaction data from CSV files stored in S3, applies data quality checks, and writes validated Parquet files to a new S3 bucket partitioned by time. This approach would replace the previous manual CSV processing workflow once fully operationalized.

flowchart LR CSV[CSV Files
S3 Raw Layer] --> Validate[Data Validation
• Schema checks
• Currency validation
• Timestamp parsing] Validate -->|Valid 98.5%| Parquet[Validated Parquet
S3 Silver Layer
Partitioned by Year/Month] Validate -->|Invalid 1.5%| Quarantine[Quarantine Layer
Error details + metadata] Parquet --> Reporting[Month-End Reporting
Single Source of Truth] style CSV fill:#f57c00,color:#fff style Validate fill:#7b1fa2,color:#fff style Parquet fill:#388e3c,color:#fff style Quarantine fill:#d32f2f,color:#fff style Reporting fill:#1976d2,color:#fff

Pipeline Run Results:

  • Run Date: January 31, 2026 (18:00 CET)
  • Data Coverage: January 1-31, 2026 (31 days)
  • Processing Duration: 22 minutes
  • Pipeline: CSV files from S3 → validation → partitioned Parquet output to S3
  • Note: This is our first production-like test run. Some metrics are expected to improve as we optimize the system.

What Changed (Before vs After):

Aspect Before After
Processing Time 2-3 days after month-end Same-day (ready by end of business day)
Reconciliation 2 days manual work 2 hours automated
Data Quality Errors found during reconciliation Errors caught automatically before reporting
Audit Trail No audit trail Full immutable audit trail
Source of Truth Multiple spreadsheets Single validated dataset

Processing Performance:

  • Data Ready For Reporting: Available same-day (January 31, 2026) — previously would have taken 2-3 days after month-end

Health Metrics Summary

graph TB subgraph Metrics["📊 Pipeline Health Metrics"] Freshness[Data Freshness
✅ Green
Current as of Jan 31 18:00] Completeness[Completeness
⚠️ Amber
98.5% vs 99.5% target] Reconciliation[Reconciliation
⚠️ Amber
€350 variance vs €100 target] Exception[Exception Rate
✅ Green
0.12% vs 0.5% target] Processing[Processing Time
✅ Green
22 min vs 30 min SLA] Compliance[Compliance
⚠️ Amber
Audit trail in progress] Cost[Cost
✅ Green
€2.80 per M records] end subgraph Status["🎯 Overall Status"] Overall[⚠️ AMBER
System Functional
Improvements Needed] end Freshness --> Overall Completeness --> Overall Reconciliation --> Overall Exception --> Overall Processing --> Overall Compliance --> Overall Cost --> Overall style Freshness fill:#2e7d32,color:#fff style Completeness fill:#ffa000,color:#111 style Reconciliation fill:#ffa000,color:#111 style Exception fill:#2e7d32,color:#fff style Processing fill:#2e7d32,color:#fff style Compliance fill:#ffa000,color:#111 style Cost fill:#2e7d32,color:#fff style Overall fill:#ffa000,color:#111
Metric Value Target Status
Data Freshness Current as of January 31, 2026 18:00 CET < 1 hour behind ✅ Green
Completeness 98.5% (1,427,700 of 1,450,200 expected) > 99.5% ⚠️ Amber
Reconciliation Match within €350 Within €100 ⚠️ Amber
Exception Rate 0.12% (2,200 records) < 0.5% ✅ Green
Processing Time 22 minutes < 30 minutes (SLA) ✅ Green
Compliance Readiness Audit trail in progress Yes ⚠️ Amber
Cost €2.80 per million records Stable ✅ Green

Overall Status: ⚠️ Amber - System functional, improvements needed

Summary:

  • Total Records Received: 1,450,200
  • Successfully Processed: 1,427,700 (98.5%)
  • Quarantined (Invalid Data): 22,500 records (1.55%)

Error Categories (Top 3):

  • Invalid Currency: 1,800 records (0.12% of total)
  • Issue: Currency codes not in ISO-4217 standard (mostly "XBT" codes and some typos)
  • Previously: These errors would have been caught manually during reconciliation (2-3 days later)
  • Now: Caught automatically before reporting, excluded from analysis
  • Missing Required Fields: 350 records (0.02% of total)
  • Issue: Missing transaction amount or date fields
  • Invalid Timestamp: 50 records (0.003% of total)
  • Issue: Dates in incorrect format or future dates

Areas for Improvement (First Run Observations):

  • Completeness: 22,500 records (1.55%) were not processed due to data quality issues. We're working with source teams to understand and resolve these patterns.
  • Reconciliation Variance: €350 difference between systems (target: €100). Initial investigation suggests timing differences in how transactions are recorded. We'll refine matching logic in next iteration.
  • Compliance Readiness: Audit trail functionality is implemented but still being validated. Expected to be complete by next run.

Single Source of Truth:

Once operationalized, this validated dataset would serve as the single source of truth for all month-end reporting, replacing the previous manual CSV processing workflow and eliminating the "numbers don't match" issue between Finance and Product reports.

Expected Impact on Your Workflow (Once Operationalized):

  • Month-end close: Would complete on day 1 instead of day 3-4
  • Reconciliation: Would be reduced from 2 days to 2 hours
  • Reporting: Month-end reports would pull from this validated source automatically
  • Data Quality: Issues would be caught before reporting, not during reconciliation

Next Steps:

These results demonstrate the pipeline's capability to process January 2026 transaction data. While some metrics need improvement, the system successfully processed 98.5% of records and caught data quality issues automatically. The validated dataset from this run is available for review and testing. We'll address the completeness and reconciliation variance issues before the next run.

If Issues Found:

If currency mapping is provided for the invalid codes, we will reprocess the affected records to include them in future reports. Data Quality Team is investigating quarantined records and will coordinate resolution with source teams.

Questions? Contact the Data Platform Team for detailed metrics or support.

Best regards, Stephen