Step I - Project Presentation
Telco Analytics
Purpose
Investment optimization and generation of new revenues to support Digital Transformation based on Data
Project Keys
1- Semantic Data Integration 2- Analytics - Correlação de Dados 3- Advanced Anomaly Detection 4- Embedded IoT Analytics to the Edge 5- Machine Learning 6- Open Data - For Peoples (PL 53/2018) 7- Decision Management 8- Immersive User Experience 9- Geospatial And Location Intelligence 10- Digital Twins
Presentation
Link to the presentation [1]
Step 2 - Studies
Usable Books
Open this Drive Link to find 3 books [2] : * Data Mining for the masses 2nd edition * Python for data Analysis * Data Mining concepts and techniques
Methodology
CRISP-DM stands for cross-industry process for data mining.
The CRISP-DM methodology provides a structured approach to planning a data mining project.
Phase of the process:
1- Business understanding
2- Data understanding
3- Data preparation
4- Modeling
5- Evaluation
6- Deployment
Step 3 - Business Case Example
Benefits to anyone who offers this solution
Offer a machine learning Template for data mining in order to:
* Improve the broadband customer experience
* Remote data management and processing with IoT optimizing investments
* Network scanning for monitoring, testing and predicting events.
Benefits to the user
Make Intelligent predictions more faster.
Business Models
We can use some Classification models Like:
- Random Forest
- Decision Tree
- XGBoost
Step 4 - Business-oriented prototype
Scoop
Join Statistics and programming to better understand huge Data and make decisions in order to improve the company.
Technical details
Tools for Studing Steps: * Knime * Anaconda / Jupyter notebook : Python users * R studio : R users
Tools for Collaborative Work: * Data Lake / DW : data extraction * Google Data Studio : Data visualization * Google Colab: Python users * Rstudio Cloud : R users
Cronograma Macro
Histórico