The main goal is to with techniques and strategies for Transforming and Analyzing Data with SQL

• Creation of tables using scripts that can be seen on the file create_tables.md
• Upload data using postgres \COPY option to import csv files. I also used the wizard from the Postgres GUI for some files.

• Check the table content to compare rows and check if the files imported correctly and have the right values.
• Review tables duplication and data cleaning details on cleaning_data.md.

-Reply questions related to data structure and values for more details go to starting_with_questions.md.

• Reply all information need of this section. More information can be found under starting_with_data.md.

• Describe the QA process and queries used, more details on this file QA.md.

• The data allowed me to reply the questions related to the project.
• The details of those questions can be found under this two sections:
  • starting_with_questions.md.
  • starting_with_data.md.

• The challenges that were faced are:
  • The data type for each column on the CSV was not defined and had to change some tables after creation during import.
  • The values of unit price, revenue and related were multiplied by a million and had to change them in order to get better results.
  • The table analytics had millions of duplicated values that needed to be cleaned from the table to get better results.

• Create primary keys on the tables.
• Create a relationship map and do normalization of the tables.
• Define restrictions to not allow NULL values in some important fields.