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Here’s a cleaned-up, professional business technical report version with clear structure, neutral tone, and corrected terminology. I preserved the technical meaning while making it suitable for stakeholders and auditors.

Preliminary Technical Verification Report

Subject: Sybase to Oracle Data Verification – Initial Findings (US_3, Last 7 Days)

1. Executive Summary

As part of the ongoing verification of US_3 Sybase data against the corresponding Oracle datasets for the last seven days, several discrepancies (“violations”) have been identified.
Some of these findings are expected and manageable, while others may pose a negative operational risk and require immediate attention.

This document summarizes the preliminary results. The investigation is still in progress, and additional findings may emerge as the verification window is expanded.

2. Scope of Verification

  • Source system: Sybase
  • Target system: Oracle
  • Time range analyzed: Last 7 days

  • Verification focus:

    • Data consistency
    • Schema alignment
    • Record availability
    • Timestamp accuracy

3. Positive / Expected Violations

The following discrepancies were identified and are considered non-blocking, provided appropriate handling is applied.

3.1 Column Length Differences

  • Multiple table columns have had their field lengths increased in Oracle, with many mapped to VARCHAR2(100).
  • During comparison, data truncation cases were detected, where Sybase text values were shorter than their Oracle counterparts.

  • Impact:

    • No data loss observed in Oracle.
    • Required an update to comparison logic to accommodate shorter Sybase field lengths.

3.2 Missing Records Due to Retention Policies

  • Certain records in specific tables were not found in Oracle.
  • These records are likely removed due to time-to-live (TTL) / data recycling policies.

  • Impact:

    • Expected behavior.
    • No corrective action required at this stage.

3.3 Timestamp Precision Differences

  • Datetime fields do not consistently match at the millisecond level.

  • Impact:

    • Required adjustments to the existing “fuzzy” comparison logic to allow acceptable time tolerances.
    • Considered manageable and expected in cross-platform comparisons.

4. Negatively Impacting Violations

The following findings present potential risks and require attention.

4.1 Column Order Mismatch Between Sybase and Oracle

  • In several tables, the column order in Oracle differs from Sybase.

  • Example:

    • Table: ZOrderDetail
    • Sybase order:
    • BOOKINGTYPE → CLIENTRECEIVEDTIME
    • Oracle order:
    • CLIENTRECEIVEDTIME → BOOKINGTYPE

Impact Analysis

  • The Sybase dump load into Oracle is not directly affected, as column mapping is performed by column name, not position.

  • However, downstream JDBC (or similar library) processing may be negatively impacted if:

    • Columns are accessed by index rather than by name.
    • Example:
    • JDBC expects column index 142 to be BOOKINGTYPE, but in Oracle it is now 143.

4.2 High-Risk Scenario: Same Data Types

  • The risk is significantly higher when misordered columns share the same data type (e.g., VARCHAR2).

  • In such cases:

    • No runtime error may occur.
    • Incorrect data may be silently written or processed, leading to data corruption and difficult-to-trace issues.

5. Recommendation

The prudent and recommended approach is to:

  • Align Oracle column order to be identical to Sybase for all corresponding tables.

  • This alignment will:

    • Prevent current and future JDBC-related issues.
    • Reduce the risk of silent data corruption.
    • Improve long-term maintainability and integration stability.

6. Next Steps

  • Verification activities are ongoing.
  • Additional analysis over a broader historical range (beyond 7 days) is required to fully assess all tables and trends.
  • Further findings and recommendations will be communicated in subsequent reports.

Status: Preliminary
More updates to follow.

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