Duration
3 days
Course Overview
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.
A combination of lecture content and lab work helps attendees achieve the following:
- 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 Platform Analytics data visualizations
- Add filters to the dashboard and share with stakeholders
Who Should Attend
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.
Prerequisite
- A basic level of familiarity with the ServiceNow application is required. New ServiceNow users should complete the ServiceNow Foundations – a self-paced introduction to the ServiceNow platform, interface, and navigation.
- Attendees should have completed the ServiceNow Fundamentals course and have some experience with ServiceNow; advanced experience is not necessary.
- A high-level overview of the Performance Analytics architecture, components, data flow, stakeholders, and deployment process is required to get the most out of the Performance Analytics Fundamentals class. New Performance Analytics users should complete the Performance Analytics Essentials – a self-paced, on-demand eLearning.
Course Follow-up
The Performance Analytics Advanced course is recommended for a more in-depth understanding and advanced Performance Analytics use case implementation.
Hands-On
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.
Course Flow
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:
Lab 2.1: Performance Analytics Data Collection
Module 3: Using the Analytics Hub
Objectives: Learn about performing 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, and 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: Breakdown Management
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
Module 7: Displaying Actionable Data
Objectives: Discover how to refine Performance Analytics data to make it more meaningful and useful by using Targets, Thresholds, Time Series, Trends, Breakdowns, and Elements Filters.
Lab work:
Lab 7.1: Indicator Targets
Lab 7.2: Indicator Thresholds
Lab 7.3: Time Series and Element Filters
Module 8: Data Visualizations and Dashboards
Objectives: Build dashboards and add data visualizations to create a role-oriented dashboard. Explore Platform Analytics Experience components like Analytics Center and Library. Dig deeper into library components which include Dashboards and Data Visualizations.
Lab work:
Lab 8.1: Data Visualizations and Dashboards
Lab 8.2: Dashboard Filters and Sharing Options
Programme scope, delivery arrangements and suitability are confirmed during enquiry.