Equipment failure is a major cause of downtime in the telecommunications industry, which can result in significant financial losses and customer dissatisfaction. To minimize downtime and ensure optimal performance, it is crucial to identify potential equipment failures and schedule maintenance accordingly proactively. This requires the collection and analysis of large amounts of data generated by various equipment and network sensors.

The deliverable for this project is a data pipeline that can efficiently collect, clean, and analyze equipment and network sensor data.

• The pipeline should be designed to identify potential equipment failures and schedule maintenance proactively, minimizing downtime and improving overall equipment performance.
• The data pipeline will be built using Python and PostgreSQL

datasets used in this project can be obtained at (https://bit.ly/3YNdO2Y)