--1-- Relational DB concepts & terminology Python syntax, data types, iteration and conditional constructs, structures, libraries
--2-- Functions, classes, objects and packages File handling, lists, store, access and manipulate data
--3-- "DW fundamentals: Components of a Data Warehouse Concept & terms Dimensional modeling (Kimball’s Approach) Inmon's Approach " "DW Fundamentals: Fact Tables for Measurements Dimension Tables for Descriptive Context Facts and Dimensions Joined in a Star Schema All DW Schemas"
--4-- "DW development with Python: Review the Business Requirements Data Profiling Design / Develop the Dimensional Model"
Session A 5 exercises
Session B
--5-- Data Marts: Data Marts & Design Considerations ETL: ETL and Techniques
--6-- Moving the Data into the DW: Extract-Transform-Load processes with Python
--7-- "Numpy Library Scipy Library"
--8-- Pandas Library
--9-- Data Visualization Principles Matplotlib Reporting & Dashboards