improved version

README.md

@@ -1,5 +1,4 @@
-#-------- Data_Engineering_project*-------------------------------------------------------------------------------------------------------
-
+# Data_Engineering_project*
 
 This repository is composed of two mini-projects where we'll assume the role of a data engineer.
 
@@ -11,17 +10,17 @@ ETL does exactly what the name implies. It is the process of
 - Transforming it into one specific format, and
 - Loading it into a database or target file.
 
-#-------------------------------------------------First scenario--------------------------------------------------------------------------
+## First scenario
 
-Assume working at a start-up devolopping an AI tool to predict if someone is at Risk for diabetes using height and body weight.
-The goal is to implement an ETL to get data from multiple sources (csv, json, xml file format), transforming it and store it in 
-a format acceptableby the AI.
+The first exemple assumes working at a start-up devolopping an AI tool to predict if someone is at Risk for diabetes using height
+and body weight. The goal is to implement an ETL to get data from multiple sources (csv, json, xml file format), transforming it
+and store it in a format acceptableby the AI.
 
 A second exemple of car-dealer campany is also given.
 The dataset contains CSV, JSON, and XML files (three from each format) for used car data which contain features named car_model, year_of_manufacture, price, and fuel. The Goal is to implement a simple ETL to collect, combine and transform data then store it
 into one file for end-user (a data analyst, scientist for analysis or a BI enginner for ad-hoc reporting).
 
-#-------------------------------------------------Second scenario-------------------------------------------------------------------------
+## Second scenario
 
 Assume working for an international financial analysis company. the company tracks stock prices, commodities, forex rates, inflation rates.  the job is to extract financial data from various sources like websites, APIs and files provided by various financial 
 analysis firms. After collectting the data, and extracting the data of interest to the company and transforming it based on the requirements given. I'll store the data in a csv file ready to be loaded into a database.