For a company that gives higher education institutions the analytical tools to decide when to start, stop, keep, or grow their academic programs in accordance with the job positions that exist in various websites (Job Postings) that are automatically downloaded through scrapping techniques for each county in the United States, a semantic layer was developed in Snowflake. With a contemporary architecture in the cloud ready to supply information to their analytical dashboards produced in Qlik Sense, it has been feasible to minimize information reload times from 11 hours to only 2 hours while processing more than 3 billion data.

The data strategy was created with a semantic intermediate layer and snowflake to centralize the data from all dental clinical branches that were stored in Odoo and PostgressSQL. Tableau dashboards were created for the operational business areas (appointment monitoring, type of diagnosis, patient waiting times, etc.), commercial indicators (revenue by specialty, treatment, branch, etc.), and financial dashboards to have their income statement reports at both corporate and branch levels.