Table of contents

• Introduction
• 1. Reporting Data
  • 1.1 Reporting Schedules
  • 1.2 Live & Baseline Revisions
  • 1.3 Activity Reporting
• 2. Planning Data
  • 2.1 Planning Schedules
  • 2.2 Activity Planning
  • 2.3 Resource Management
• 3. Metadata & Custom Fields
  • 3.1 Metadata Fields
  • 3.2 Metadata Values
• Conclusion

Introduction

ILAP Analytics provides planners and analysts with a structured view of key reporting, planning, and metadata information. This article outlines the types of data available in ILAP Analytics, helping lead planners understand what they can request from BI mechanics and application developers to generate dashboards and reports.

1. Reporting Data

Reporting data in ILAP Analytics focuses on tracking schedules, performance metrics, and revisions. This includes:

1.1 Reporting Schedules

• ReportScheduleType – Defines types of schedules.
• Reporting_Schedule – Stores information on scheduled reports, including:

  • Planned & Actual Work Hours (e.g., TotalWorkHours, ActualWorkHours)

  • Performance Metrics (e.g., ProductivityCumulative, PerformanceCumulative)

  • Baseline & Revisions (e.g., BaselineScheduled, FinishBaseline)

1.2 Live & Baseline Revisions

• Reporting_BaselineRevision – Stores historical baselines for performance tracking.
• Reporting_LiveRevision – Captures ongoing updates and schedule changes.

1.3 Activity Reporting

• Reporting_Activity – Tracks scheduled and completed activities with:

  • Time Allocations (e.g., Start, Finish, ActualWorkHours)

  • Metadata & Labels for categorization.

2. Planning Data

Planning data in ILAP Analytics provides detailed insights into schedules, activities, and resource management.

2.1 Planning Schedules

• Planning_Schedule – Contains high-level planning details:

  • Current Progress Tracking

  • Completion Dates & Baselines

  • Labels & Metadata for Categorization

2.2 Activity Planning

• Planning_Activity – Provides information on scheduled tasks, including:

  • Early & Late Start Times

  • Remaining & Planned Hours

  • Constraints such as “Must Start After”

2.3 Resource Management

• Planning_ResourceAssignment – Maps activities to specific resources.
• Planning_Resource – Defines available resources.

• Planning_Calendar – Structures work periods, including:

  • Weekly Repeating Periods

  • Connected Time Slots

3. Metadata & Custom Fields

Metadata in ILAP Analytics enables flexible data structuring through custom attributes.

3.1 Metadata Fields

• Planning_MetadataField – Defines additional custom fields for planning.
• Reporting_MetadataField – Stores extra reporting parameters.

3.2 Metadata Values

• Planning_ActivityMetadataFieldValue – Links metadata to planning activities.
• Reporting_ScheduleMetadataFieldValue – Assigns metadata values to reporting schedules.

Conclusion

ILAP Analytics provides a structured and comprehensive dataset for analyzing planned and actual work, performance tracking, scheduling, and resource allocation. Lead planners can request dashboards based on these datasets to gain insights into project progress, efficiency, and forecasting. Understanding these data structures helps in forming precise BI requests for better decision-making.