Telecom Company

1 - Field Service (Odoo):
+7,000 daily field activities
+450 brigades for field activities

2- Enterprise Data Warehouse: 
The goal of the project was to have access to analytical models that would provide a comprehensive understanding of ANTEL's overall situation regarding strategic issues facing the Chairman, Directors, CEO, and Management. This includes analyzing Procedures, Claims, Clients, Products, Services, and Billing. Creation and ongoing development of consolidated information from all ANTEL's internal systems. This  includes data on Claims, Client Portfolio, Product Offers, Procedures, and Billing for Data,  Fixed Telephony, and Mobile Telephony.

3 - Development and subsequent maintenance of the various systems that involve Java technology are carried out:

• Cellular Radio Base claims management (Intranet)
• Entry of commutation claims to the SGT (Intranet)
• System for Monitoring and Control of Data Network Works used by officials of  the Technical Development Division of ANTEL

4 - Data Science: 

A data governance framework was built to manage the use of the data within the platform.This governance framework involved the definition of the data cataloging processes, self-service processes, Data Architecture design, evaluation of the different technological tools  for the management of the catalog and data lineage, establishment of metrics and controls,  as well as the continuous monitoring of the practices defined for the improvement of the  processes. Subprojects included:
• AI and Data Science during COVID19: mobility and residence along the country. Information used by the National Health Ministry and the National  Statistical Institute.
• Technology and tools used: Hortonworks Data Platform, HDFS, Hive, NIFI,  Jupiter Notebook, Spark, Tableau.
• Workforce Management
• Budget Management (budget vs reality)
• Balanced Scorecard Design and Implementation 

5 - Big Data:
Quanam was responsible for the data lake implementation and associated  analytical and advanced analytical solutions. At the same time, we participate in the  implementation of the Data Lake Data Governance Strategy by defining policies,  processes and controls to measure compliance for ingestion, self-service, catalogue,  security and data quality. Some of the use cases we implemented through Machine  Learning Models are: 

• Debt forecast.
• Personalized product recommendation and shows (ANTEL owns an Arena).
• Churn Model
• Customers scoring for customer value ranking
• Intelligent Territory is an Integral Technology Platform that provides information about the flow of citizenship