Experiment #208

Automatic Calendar Scheduling

The purpose of the #208 experiment is to use Artificial Intelligence to solve problems related to schedule management with an Automatic Calendar Schedule by prioritizing tasks based on resources, availability and employee capacity. Early planning can provide numerous benefits such as covering more tasks, improving worker efficiency and performance, as well as meeting all deadlines.

Project Date: July – August 2022

Services: Power BI – Azure Machine Learning – Azure Data Factory – Azure SQL Server

Technology used: Data Analytics – Artificial Intelligence

Challenge

Using AI to solve problems with the management of an Automated Calendar

Idea &
process

The main idea was developed due to the need to anticipate the scheduling of tasks to avoid the misuse of human and economic resources, whose causes are mainly deficiencies in the planning of schedules or due to unexpected incidents.

The origin of the data lies in the user’s own planning and distribution of all the company’s tasks.

This information will be stored through an application in a database in Azure.

Subsequently, every time planning is required, ad-hoc models made in Python scripts will be executed, creating the calendar with the personnel and the tasks they will perform.

Finally, all the information gathered by the models will be stored in the company’s Data Warehouse, which will feed the relevant management applications, Power BI reports, and so on.

Utility

Using AI to solve problems with the management of an Automated Calendar

Utility

Anticipating emerging problems in task planning, as well as having the ability to replan in seconds, has significant benefits:

Increasing the efficiency of the planning department, reducing the economic cost due to increased staffing, and creating the most optimal planning possible to be able to supply the needs of our business.

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