Table of contents

• Introduction
• The value of Background Jobs
• List of Background Jobs
  • Job 1: Archive Previous Report Schedule Representations
  • Job 2: Persist Schedule Data
  • Job 3: Update Report Activities
  • Job 4: Calculate KPIs
  • Job 5: Save Field Values
  • Job 6: Periodize Hours and FTEs
  • Job 7: Calculate Actuals
  • Job 8: Aggregation and Calculations
  • Job 9: Remove Temporary ILAP File

Introduction

In ILAP Analytics, background jobs play a critical role in processing ILAP files after they are received. These jobs ensure that schedules, activities, and related data are appropriately stored, updated, and prepared for analysis. Understanding these processes provides valuable insight into how ILAP Analytics handles data ingestion and management.

The value of Background Jobs

The background jobs are vital to ensuring that ILAP Analytics operates smoothly and efficiently. They:

• Preserve historical data for reference and audit purposes.

• Maintain the accuracy and integrity of schedules and activities.

• Process key metrics and aggregations that are essential for reporting and decision-making.

• Ensure data is cleanly stored and accessible for consumers and external systems.

By automating these processes, ILAP Analytics minimizes manual intervention while maximizing the reliability and consistency of schedule data management.

When an ILAP file is published to ILAP Analytics—whether through IDE, ILAP Adapter, or a middleware solution like TIE—the system temporarily stores the file before initiating a series of background jobs. These jobs are executed in sequence to process the schedule data and update the system.

List of Background Jobs

Job 1: Archive Previous Report Schedule Representations

Process: ArchivePreviousReportScheduleRepresentationsAsync
Before the new schedule data is appended, existing reporting objects are archived. This ensures that previous versions of schedules, activities, metadata, and periodization are preserved for historical reference.

Job 2: Persist Schedule Data

Process: CreateDataAsync
All schedule data—including schedules, activities, resources, calendars, work patterns, and profiles—are persisted to the database. This step ensures the integrity and availability of the core schedule data.

Job 3: Update Report Activities

Process: ReportActivitiesAsync
The activity list within the report is updated:
- New activities are added.
- Existing activities are updated.
- Removed activities (no longer part of the latest schedule) are marked as deleted.
This step also updates schedule core data, such as start/finish dates, total hours, earned hours, actual hours, and float values.

Job 4: Calculate KPIs

Process: GenerateReportKpisAsync
Currently inactive, this job is designed for future use, where metrics and KPIs will be calculated and updated based on schedule data.

Job 5: Save Field Values

Process: GenerateReportMetadataAsync
Field values for schedules and activities are received and stored. In future versions, this job will include all field values for all known ILAP terms, beyond those linked to specific schedule types.

Job 6: Periodize Hours and FTEs

Process: PeriodizeReportSchedule
This job connects to a time-phasing service to:
- Send activity, calendar, and profile data.
- Receive and store periodically planned hours and full-time equivalents (FTEs) for all activities.

Job 7: Calculate Actuals

Process: CalculateActuals
For LIVE schedules, this job processes the latest received actual expended hours, progress, and earned hours, storing this data in the periodized dataset.

Job 8: Aggregation and Calculations

Process: SetExtendedPropertiesAsync
Aggregated calculations, such as metrics, measures, and derived columns, are processed and stored for reporting and analysis.

Job 9: Remove Temporary ILAP File

Process: MoveAndClearIlapFileContentAsync
Once all the above steps are completed, the temporary ILAP file is removed from storage to free up resources and maintain system cleanliness.