Más contenido relacionado


  1. Artificial Intelligence is key to data analytics in giving suggestions to improve the project success rate throughout the project lifecycle. Business intelligence refers to the procedural and technical infrastructure that collects, stores, and analyzes the data produced by a company's activities. Business analytics refers to the skills, technologies, and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning based on the data derived. Every company thrives in its business when there is proper project management in place. This, however, is seen seldom, because of the large amount of project failure rates. Project managers have slowly run out of options but to turn to data and data analytics for help. The importance of data analytics in project management Digital Projects Matching resources Allocating the best resources to the Scheduling available resources. Managing real time data Managing risks, issues and test cases, etc. stakeholders Features of Digital Projects in KTern.AI KTern.AI Digital Projects UVP Impact of data analytics on project managers AI, BI and BA Roles and responsibilities of a project manager Everyday work item analytics Test analytics Business process insights Sprint reports Project signoff reports Project and process reports etc Smart project charter and Intelligent risk management to improve the Communication and Scope control for the Project Execution. Project auto-simulation planner and Timeline auto-tracker with insights for better version management linked to the Project Milestones. Sign-off approval auto-orchestrator and Q-gate auto-integration for conformance to compliance and auto validations. The project manager has the highest dependency in line with project management. This encloses the initial process of project planning to proper management through all the phases of the project until project completion. Talking about projects of any altitude, a large project like a conversion project from ECC to S/4HANA has much more elaborate and stretched list of deliverables, and without data analytics, it would turn tedious.