Semiconductor manufacturing

Next-day visibility into missed data processing

Client profile

a global semiconductor company · Sales and service operations data · Embedded SQL Server / SSIS engineer · Ongoing

Semiconductor · ETL operations · SQL Server

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01 / Inside the engagement

Situation

SSIS and SQL Server supplied operational data to sales and service-planning reports. The team needed a daily check for files that had not been processed, including cases where a job did not report an error.

Conceptual delivery summaryIncident-proven detection

Before

  1. Source files
  2. SSIS processing
  3. SQL Server reports

After

  1. Source files
  2. SSIS and daily absence checks
  3. Reports and alerts

Simplified workflow. The case text describes the contribution, delivery stage and evidence.

Explore the full conceptual diagram
Next-day visibility into missed data processingBefore: Source files to SSIS processing to SQL Server reports. After: Source files to SSIS and daily absence checks to Reports and alerts. BEFORE AFTER Sourcefiles SSISprocessing SQL Serverreports Sourcefiles SSIS and dailyabsence checks Reportsand alerts
Conceptual illustration of the engagement. The delivery stage and measurement scope are described in this case study.

02 / Inside the engagement

What UTIS did

  • UTIS improved the file-processing bottleneck and optimized the SSIS packages.
  • Added an alerting check for files not processed on the previous day, alongside investigation of processing issues.
  • Documented the system and its operating steps for a planned cloud migration.

03 / Inside the engagement

Results

  • A subsequent real incident confirmed that the monitoring check could identify missed processing the next day.
  • The identified issue was resolved the same day it was found.

Why it matters to you

A job can finish without processing the data a report needs. Checking expected work as well as error messages gives operators a way to investigate missing processing. The documented result is one incident, not a guarantee for every failure.

Stack

SQL ServerT-SQLSSISAlerting and root-cause analysisSLA management

How we measured it: incident-proven next-day detection in a real incident, followed by same-day resolution. This evidence describes the observed incident, not a service-level commitment or detection guarantee.

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