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| PROJECT 13

Data-Engineering-Pipeline

Creating a Data Pipeline for Stock Data

In this project, I have performed the following tasks:

  1. Fetching data from APIs
  2. Dump it into the cloud (Databricks folder)
  3. Start cleaning the data, transforming from json to data frame, correcting data types, dropping unwanted observations
  4. Gathering the different stocks in a single dataset, joining and calculating some indicators like moving averages and Relative Strength Index (RSI)
  5. Sending the data to a PostgreSQL database for consumption
  6. Connecting with Power BI and creating a final report for insights.

For full description of the project, step-by-step, visit the Medium Post.