Ignio Ai.Workload Management - Intermediate
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.24 GB | Duration: 7h 48m
Learn how ignio makes predictable, agile and silent batch operations
What you'll learn
Explain the concepts of product overview
Demonstrate the user journey of all key functions of the product
Describe the concepts of the user journey
Explain and show how ignio AI. Workload Management makes the batch from reactive to proactive
Requirements
100% completion of ignio Overview course
100% completion of ignio AI. Workload Management - Foundation course
Description
This course provides an detail study on ignio AI.Workload Management. It first covers product overview, then does a deep-dive into 6 user journies. This course does a deep dive into each of these journeys explaining the core concepts through a product demo.------------------------------------------------------------------------------------------------------------------------------------Digitate™ leverages machine learning and AI (artificial intelligence) to intelligently manage IT and business operations. Our award-winning product, ignio™, is a cognitive automation solution that helps IT rapidly identify and remediate outages in minutes. ignio's unique pre-built knowledge allows customers to realize the value of AI in significantly less time than other solutions. It binds together disparate but interconnected business applications, processes, and the underlying infrastructure to drive smart decisions and perform actions autonomously. Our suite of product includes: - ignio™ AIOps - Map business applications and the underlying infrastructure to identify the root cause of a problem and perform autonomous remedial actions - ignio™ AI.WorkloadManagement - Minimize time needed for planning and operational activities with risk assessment, preventive recommendations & prediction of future batch job impacts with over 90% accuracy to reduce SLA violations - ignio™ AI.ERPOps - Provide functional and technical relationship mapping, rapidly identify and rectify typical issues impacting business and stay on top of compliance issues - ignio™ AI. Digital Workspace - A self-healing, end-user experience management product - ignio™ Cognitive Procurement - An AI based oversight mechanism into the Procure-to-Pay function that detects and predicts different types of procurement anomalies on time - ignio™ AI.Assurance - Enables enterprises to align quick delivery of quality software with some of its distinguished features such as autonomous test suite generation, impact analysis, and self-healing capabilities Digitate was founded in 2015 and is headquartered in Santa Clara, California, and Pune, India.
Overview
Section 1: Product Overview
Lecture 1 WLM Product Overview - Concept
Section 2: User Journey 1 - Monitor and Notify Anomaly
Lecture 2 Concept
Lecture 3 Implementation Journey
Lecture 4 Prepare and Ingest Data
Lecture 5 Data Analysis, Mine Intelligence and View Results
Lecture 6 Scheduling Analysis
Lecture 7 Configure and Validate Notifications
Lecture 8 Measuring Effectiveness and Scaling Implementation Scope
Section 3: User Journey 2 - Predictions and Look Ahead of SLAs
Lecture 9 Concept
Lecture 10 Implementation Journey
Lecture 11 Prerequisites
Lecture 12 Prepare and Ingest
Lecture 13 Run Analysis
Lecture 14 How to Configure
Lecture 15 How to view results - Conclusion
Lecture 16 Best Practices
Lecture 17 Scale
Section 4: Plan for Growth and Change
Lecture 18 Concept
Lecture 19 Overview
Lecture 20 Run Analysis
Lecture 21 How to view results
Lecture 22 Other Information
Section 5: Drive Continous Improvements
Lecture 23 Concept
Lecture 24 Overview
Lecture 25 Run and Schedule Analysis
Lecture 26 How to Configure
Lecture 27 View Results
Lecture 28 Scale Best Practices
Section 6: Diagnose and Resolve Failures
Lecture 29 Concept
Lecture 30 Overview
Lecture 31 Prerequisites
Lecture 32 Model Extensions
Lecture 33 Configure and Validaiton
Lecture 34 Best Practices & Effectiveness
Section 7: Manage Alerts
Lecture 35 Concept
Lecture 36 Overview
Lecture 37 Run Analysis
Lecture 38 Configure Policies
Lecture 39 How to view
Lecture 40 Conclusions
Batch Operators, Batch Architect
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