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Performance Analytics (PA) Essentials
Code:
PA Funds
Duration:
2 Day
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$1700
USD
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Performance Analytics provides simple access to key performance indicators (KPIs) and metrics for proactive business service improvement. In this 2-day interactive technical training, attendees master the setup, configuration, and usage of the Performance Analytics application.
Extensive hands-on exercises are included with each course module to reinforce the lecture concepts and provide practical experience. Exercises are performed in a personal dedicated training instance.
This course is available in the following formats:
Duration: 2 Day
Duration: 2 Day
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Delivery Format: Virtual Classroom
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$ 1700 |
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Delivery Format: Virtual Classroom
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$ 1700 |
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Delivery Format: Virtual Classroom
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$ 1700 |
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Delivery Format: Virtual Classroom
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$ 1700 |
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Delivery Format: Virtual Classroom
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$ 1700 |
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Delivery Format: Virtual Classroom
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$ 1700 |
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Delivery Format: Virtual Classroom
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$ 1700 |
- Identify Performance Analytics use cases, architecture, and deployment process
- Navigate the Analytics Hub (formerly the Indicator Scorecard)
- Configure and monitor Data Collection jobs
- Build Automated Indicators to track KPIs
- Enhance Indicators with Breakdowns for detailed data navigation
- Create Manual Indicators and manage manual data population
- Build Formula Indicators for added process and service inferences
- Configure Targets and Thresholds to make process visualization actionable
- Build various Performance Analytics Widgets and Reporting Filters
- Design and populate Dashboards
Module 1: Performance Analytics Introduction
Objectives:
Identify Performance Analytics key functionality, differences from operational reporting, roles, deployment, and key use cases.
Lab work:
Lab 1.1: Essential Concepts
Module 2: Data Collection
Objectives: Learn the basics of data collection, job configuration, and best practices. Distinguish between daily and historic collection. Discuss data management and retention practices.
Lab work:
Module 3: Analytics Hub
Objectives: Learn about performing a detailed analysis and comparison of Indicator data using the Analytics Hub. View indicator data and statistical summaries, use Confidence and Prediction bands, understand Time series aggregations and Breakdowns, create and view Targets, Thresholds, and Comments.
Lab work:
Lab 3.1: Analytics Hub Navigation
Module 4: Automated Indicators
Objectives: Configure Automated Indicators and Indicator Sources. Practice form-based and assisted Indicator creation using the built-in Indicator creation workflow.
Lab work:
- Lab 4.1: Automated Indicators
Module 5: Automated Breakdowns
Objectives: Configure Breakdowns, Breakdown Sources, and Breakdown Mappings. Manage Breakdowns using the Breakdown matrix and Breakdown Matrix exclusions.
Lab work:
- Lab 5.1: Automated Breakdowns
- Lab 5.2: Managing Breakdowns
Module 6: Formula and Manual Indicators
Objectives: Learn about Manual indicators and their use cases. Discuss manual breakdowns in the context of manual indicators. Learn about formula indicators and the basics of formula syntax.
Lab work:
- Lab 6.1: Formula Indicators
- Lab 6.2: Manual Indicators
Module 7: Displaying Actionable Data
Objectives: Discover how to refine Performance Analytics data to make it more meaningful and useful using Targets, Thresholds, Time Series, Trends, Breakdowns, and Elements Filters.
Lab work:
- Lab 7.1: Targets
- Lab 7.2: Thresholds
- Lab 7.3: Element Filters
Module 8: Widgets and Dashboards
Objectives: Build dashboards and add widgets to create a role-oriented dashboard. Explore Dashboard Administration, Responsive Canvas, adding Reports to dashboards and using Interactive filters, and In-Form (Context-Sensitive) Analytics.
Lab work:
- Lab 8.1: Dashboards and Widgets
- Lab 8.2: Data Filtering
Module 1: Performance Analytics Introduction
Objectives:
Identify Performance Analytics key functionality, differences from operational reporting, roles, deployment, and key use cases.
Lab work:
Lab 1.1: Essential Concepts
Module 2: Data Collection
Objectives: Learn the basics of data collection, job configuration, and best practices. Distinguish between daily and historic collection. Discuss data management and retention practices.
Lab work:
Module 3: Analytics Hub
Objectives: Learn about performing a detailed analysis and comparison of Indicator data using the Analytics Hub. View indicator data and statistical summaries, use Confidence and Prediction bands, understand Time series aggregations and Breakdowns, create and view Targets, Thresholds, and Comments.
Lab work:
Lab 3.1: Analytics Hub Navigation
Module 4: Automated Indicators
Objectives: Configure Automated Indicators and Indicator Sources. Practice form-based and assisted Indicator creation using the built-in Indicator creation workflow.
Lab work:
- Lab 4.1: Automated Indicators
Module 5: Automated Breakdowns
Objectives: Configure Breakdowns, Breakdown Sources, and Breakdown Mappings. Manage Breakdowns using the Breakdown matrix and Breakdown Matrix exclusions.
Lab work:
- Lab 5.1: Automated Breakdowns
- Lab 5.2: Managing Breakdowns
Module 6: Formula and Manual Indicators
Objectives: Learn about Manual indicators and their use cases. Discuss manual breakdowns in the context of manual indicators. Learn about formula indicators and the basics of formula syntax.
Lab work:
- Lab 6.1: Formula Indicators
- Lab 6.2: Manual Indicators
Module 7: Displaying Actionable Data
Objectives: Discover how to refine Performance Analytics data to make it more meaningful and useful using Targets, Thresholds, Time Series, Trends, Breakdowns, and Elements Filters.
Lab work:
- Lab 7.1: Targets
- Lab 7.2: Thresholds
- Lab 7.3: Element Filters
Module 8: Widgets and Dashboards
Objectives: Build dashboards and add widgets to create a role-oriented dashboard. Explore Dashboard Administration, Responsive Canvas, adding Reports to dashboards and using Interactive filters, and In-Form (Context-Sensitive) Analytics.
Lab work:
- Lab 8.1: Dashboards and Widgets
- Lab 8.2: Data Filtering
This course is designed for Performance Analytics Administrators and Power Users who administer and create content for the Performance Analytics application. Service owners designing KPIs and Dashboard requirements for deeper service insight will also benefit from this course.