I have been given two SQL Databases which are of same schema type but differ by table names or columns names within those tables.
I am required to analyse those data within the tables and suggest , which are the similar(based on data within the table) tables between those two databases.
Can anybody suggest me to how to move forward with this problem statement. I am new to Data Analytics using Python. It will be really helpful if someone can help me with this.
As an example : lets Consider two databases A and B . . . A contains a table called "person_details" and B contains a table called "details"
I am looking for answers where i can recomend by analyzing the data within those two tables that they can be joined.
Consider using sqlite package of python for connecting to db and querying in it. https://docs.python.org/2/library/sqlite3.html
Via query you can check the schema of tables. Or if you want to analyse data using pandas then consider using SQLAlchemy for creating connection to DB. http://docs.sqlalchemy.org/en/latest/core/engines.html#supported-databases
After that read tables as pandas DataFrame using this https://pandas.pydata.org/pandas-docs/version/0.21/generated/pandas.read_sql_table.html
from sqlalchemy import create_engine
import pandas as pd
engine_A = create_engine('sqlite:///sqlalchemy_A.db')
engine_B = create_engine('sqlite:///sqlalchemy_B.db')
data_A = pd.read_sql_table("person_details",engine_A)
data_B = pd.read_sql_table("details",engine_B)
This should work.