Week 1

• Introduction to Data Warehousing

• (Definition, history, advantages, disadvantages, benefits & concept)

• Data Warehousing Lifecycle & Rules

Week 2

• Data warehousing terminologies

• Datastore OR Data sources

• Data Mart

• Design Schemas

• Meta data

• OLTP (Online transaction processing) & OLAP (Online Analytics processing)

• ETL (Extract Transform & Load)

• Data Warehousing Architecture

• Benefits, typical architecture & Architecture flow

Week 3

• Data Warehousing modelling

• Importance

• Types of models (Or technique)

• Entity relationship Diagram & Data Flow Diagram

• Dimensional modelling

• Facts & Dimension

• Database Management System

• Database

• Database Management System

• Components of DBMS (Hardware, software, Data, Procedure & Data Access Lang (SQL))

• Types of DBMS (Hierarchical, Network, Relational & Object Oriented)

• Advantages of DBMS

• Application of Data warehousing & DBMS (Banking, sales, telecommunication etc.)

Week 4

• Data Access Language

• Structure Query Language (SQL)

• Data Manipulation Language (DML)

• Data Definition Language (DDL)

• Data Control Language (DCL)

• Sub queries & Constraints

• Joins & Aggregations functions/clauses

• Variant of DB SQL (Mysql, Oracle, presto)

• Introduction to python programming language

Week 5

• Data Analytics with Microsoft Excel

• Data Cleaning

• Excel Functions

• Pivot and Charts

• Lookup Functions (V & HLookups

• Excel Macros (Advance)

• Data Visualization

• Concept, tools & Applications

• Overview of Tableau

• Deep dive into Microsoft PowerBI

Week 6

• Business Intelligence (BI)

• Indepth Data Analytics

• Big Data​​​​​​​

• Overview of Big Data (Hadoop)

• Working with Data in Public Cloud (AWS)

Week 7

• SQL Extensive tutorials & Practice

• Practical Analysis with Real Life Data

• Data Analytics Task

Week 9

• 17. Preparing for Data Analysis Interview

• 18. CV Preparation

• 19. Interview Preparation (Paid Package)
  
   

This course is delivered online in an interactive format with an online live facilitator and a coordinator. We have structured the class to accommodate for working class individuals and also students who also have other commitments.

The format for the class is listed below:

• Course are delivered online via our collaboration platform (Zoom, Goto Meeting, and Google Meet)
• two class per week with a time duration of 2 - 3 hours per day
• Recorded live sessions for individuals who are unable to attend the class.
• Weekly snippets to read ahead of next class to stimulate learning (I.e. available on your user dashboard on our SwiftProfile portal)
• Group learning and discussions topics through our learning channels

Week 1
1. Introduction to Data Warehousing
(Definition, history, advantages, disadvantages, benefits & concept)
2. Data Warehousing Lifecycle & Rules
 
Week 2
3. Data warehousing terminologies
Datastore OR Data sources
Data Mart
Design Schemas
Meta data
OLTP (Online transaction processing) & OLAP (Online Analytics processing)
ETL (Extract Transform & Load)
4. Data Warehousing Architecture
Benefits, typical architecture & Architecture flow
 
Week 3
5. Data Warehousing modelling
Importance
Types of models (Or technique)
Entity relationship Diagram & Data Flow Diagram
Dimensional modelling
Facts & Dimension
6. Database Management System
Database
Database Management System
Components of DBMS (Hardware, software, Data, Procedure & Data Access Lang (SQL))
Types of DBMS (Hierarchical, Network, Relational & Object Oriented)
Advantages of DBMS
Application of Data warehousing & DBMS (Banking, sales, telecommunication etc.)
 
Week 4
7. Data Access Language
Structure Query Language (SQL)
Data Manipulation Language (DML)
Data Definition Language (DDL)
Data Control Language (DCL)
Sub queries & Constraints
Joins & Aggregations functions/clauses
Variant of DB SQL (Mysql, Oracle, presto)
Introduction to python programming language
 
Week 5
8. Data Analytics with Microsoft Excel
- Data Cleaning
- Excel Functions
- Pivot and Charts
- Lookup Functions (V & HLookups)
- Excel Macros (Advance)
9. Data Visualization
Concept, tools & Applications
Overview of Tableau
Deep dive into Microsoft PowerBI
 
Week 6
10. Business Intelligence (BI)
11. Data Analytics
12. Overview of Big Data (Hadoop)
13. Working with Data in Public Cloud (AWS)
 
Week 7
14. SQL Extensive tutorials & Practice
https://www.w3schools.com/sql/default.asp -- tutorials
https://www.w3schools.com/sql/sql_exercises.asp -- Practice/ Exercise
NB: Still need to find practice material that covers more use-cases or scenarios
 
Week 8
15. Practical Analysis with Real Life Data
16. Data Analytics Task
 
Week 9
17. Preparing for Data Analysis Interview
18. CV Preparation
19. Interview Preparation (Paid Package)

Our flexibility is not only reflected in our learning approach but also in our payments. To provide our clients with the best options, we have integrated convenience into our payments mode:

Option 1

• Full Payment

Option 2

• Half Payment (i.e. 50% at registration and 50% in the following month)

Option 3

• 3-time Part Payment (i.e. you will be able to split the payment into 3 halves being 50% at registration, 25% each in the subsequent after 4 and 2 weeks). Please note that the option 3 is only available for customers who have chosen packages worth more than £400 from our BRINT Services.

To be updated