Data Warehouse Concepts- Basic to Advanced concepts

Data Warehouse Concepts: Basic to Advanced concepts, available at $74.99, has an average rating of 3.58, with 124 lectures, 13 quizzes, based on 2819 reviews, and has 13407 subscribers.

You will learn about Learning all the concepts and terminologies related to the Datawarehouse , such as the OLTP, OLAP, Dimensions, Facts, Start Schema, Snow flake Schema etc It also explains how the data is managed with in the Data Warehouse and explains the process of reading and writing data onto the Warehouse. Later in the course you would also learn the basics of Data Modelling and how to start with it logically and physically. You would also learn all the concepts related to Facts, Dimensions, Aggregations and commonly used techniques of ETL. This course is ideal for individuals who are This Course is intended for freshers who are new to the Data Warehouse world, Application/ETL developers, Mainframe develoeprs, database administrators, system administrators, and database application developers who design, maintain, and use data warehouses. or Recent graduates looking to get a job in the IT Industry or Finance professionals wanting to learn about Data Warehouses for reporting and analysis purposes, businesses looking to update and improve on data storage, analysis, and reporting processes. It is particularly useful for This Course is intended for freshers who are new to the Data Warehouse world, Application/ETL developers, Mainframe develoeprs, database administrators, system administrators, and database application developers who design, maintain, and use data warehouses. or Recent graduates looking to get a job in the IT Industry or Finance professionals wanting to learn about Data Warehouses for reporting and analysis purposes, businesses looking to update and improve on data storage, analysis, and reporting processes.

Enroll now: Data Warehouse Concepts: Basic to Advanced concepts

Summary

Title: Data Warehouse Concepts: Basic to Advanced concepts

Price: $74.99

Average Rating: 3.58

Number of Lectures: 124

Number of Quizzes: 13

Number of Published Lectures: 122

Number of Curriculum Items: 137

Number of Published Curriculum Objects: 122

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Learning all the concepts and terminologies related to the Datawarehouse , such as the OLTP, OLAP, Dimensions, Facts, Start Schema, Snow flake Schema etc

It also explains how the data is managed with in the Data Warehouse and explains the process of reading and writing data onto the Warehouse.

Later in the course you would also learn the basics of Data Modelling and how to start with it logically and physically.

You would also learn all the concepts related to Facts, Dimensions, Aggregations and commonly used techniques of ETL.

Who Should Attend

This Course is intended for freshers who are new to the Data Warehouse world, Application/ETL developers, Mainframe develoeprs, database administrators, system administrators, and database application developers who design, maintain, and use data warehouses.

Recent graduates looking to get a job in the IT Industry

Finance professionals wanting to learn about Data Warehouses for reporting and analysis purposes, businesses looking to update and improve on data storage, analysis, and reporting processes.

Target Audiences

This Course is intended for freshers who are new to the Data Warehouse world, Application/ETL developers, Mainframe develoeprs, database administrators, system administrators, and database application developers who design, maintain, and use data warehouses.

Recent graduates looking to get a job in the IT Industry

Finance professionals wanting to learn about Data Warehouses for reporting and analysis purposes, businesses looking to update and improve on data storage, analysis, and reporting processes.

In this course, you will?learn?all the concepts and terminologies related to the Data Warehouse , such as the OLTP, OLAP, Dimensions, Facts and much more, along with other concepts related to it such as what is meant by Start Schema, Snow flake Schema, other options available and their differences. It also explains how the data is managed with in the Data Warehouse and explains the process of reading and writing data onto the Warehouse. Later in the course you would also learn the basics of Data Modelling and how to start with it logically and physically. You would also learn all the concepts related to Facts, Dimensions, Aggregations and commonly used techniques of ETL. Upon completion of this course, you would have a clear idea about, all the concepts related to the Data Warehouse, that should be sufficient to help you start off with the next step of becoming an ETL developer or Administering the Data warehouse environment with the help of various tools. All the Best and Happy Learning !

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome! Thank you for learning the Data Warehouse concepts with me!

Chapter 2: Brief about the Data warehouse

Lecture 1: Is Data Warehouse still relevant in the age of Big Data?

Lecture 2: Why do we need a Data Warehouse?

Lecture 3: What is a Data Warehouse?

Lecture 4: Characteristics of a Data Warehouse

Chapter 3: Business Intelligence

Lecture 1: What is Business Intelligence?

Lecture 2: Business Intelligence -Extended Explanation

Lecture 3: Uses of Business Intelligence

Lecture 4: Tools used for (in) Business Intelligence

Chapter 4: Data Warehouse Architectures

Lecture 1: Enterprise Architecture or Centralized Architecture

Lecture 2: Federated Architecture

Lecture 3: Multi-Tired Architecture

Lecture 4: Components of a Data Warehouse

Lecture 5: Purpose of a Staging Area in Data Warehouse Architecture – Part 1

Lecture 6: Purpose of a Staging Area in Data Warehouse Architecture – Part 2

Lecture 7: Advantages of Traditional warehouse

Lecture 8: Limitations of Traditional Data Warehouses

Chapter 5: ODS – Operational Data Store

Lecture 1: What is ODS?

Lecture 2: Define ODS

Lecture 3: Staging Vs ODS

Lecture 4: Differences between ODS,DWH, OLTP, OLAP, DSS

Chapter 6: OLAP

Lecture 1: OLAP Overview

Lecture 2: OLTP Vs OLAP – Part 1_U

Lecture 3: OLTP Vs OLAP – Part 2

Lecture 4: OLAP Architecture – MOLAP

Lecture 5: ROLAP

Lecture 6: HOLAP

Lecture 7: DOLAP

Chapter 7: Data Mart

Lecture 1: What is a Data Mart?

Lecture 2: Fundamental Difference between DWH and DM

Lecture 3: Advantages of a Data Mart

Lecture 4: Characteristics of a Data Mart

Lecture 5: Disadvantages of a Data Mart

Lecture 6: Mistakes and MisConceptions of a Data Mart

Chapter 8: Metadata

Lecture 1: Overview of Metadata

Lecture 2: Benefits of Metadata

Lecture 3: Types of Metadata

Lecture 4: Projects on Metadata

Lecture 5: Best Practices for Metadata Setup

Lecture 6: Summary

Chapter 9: Data Modeling

Lecture 1: What is Data Modeling?

Lecture 2: Data Modeling Techniques

Chapter 10: Entity Relational Data Model

Lecture 1: ER – (Entity Relation) Data Model

Lecture 2: ER Data Model – What is Entity?

Lecture 3: ER Data Model – Types of Entities – Part 1

Lecture 4: ER Data Model – Types of Entities – Part 2

Lecture 5: ER Data Model – Attributes

Lecture 6: ER Data Model – Types of Attributes

Lecture 7: ER Data Model – Entity-Set and Keys

Lecture 8: ER Data Model – Identifier

Lecture 9: ER Data Model – Relationship

Lecture 10: ER Data Model – Notation

Lecture 11: ER Data Model – Logical Data Model

Lecture 12: ER Data Model – Moving from Logical Data Model to Physical Data Model

Lecture 13: ER Data Model – Differences between CDM, LDM and PDM

Lecture 14: ER Data Model – Disadvantages

Chapter 11: Dimensional Model

Lecture 1: What is Dimension Modelling?

Lecture 2: Benefits of Dimensional Modelling

Lecture 3: What is a Dimension?

Lecture 4: What is a Fact?

Lecture 5: Additive Facts

Lecture 6: Semi Additive Facts

Lecture 7: Non-Additive Facts

Lecture 8: FactLess Facts

Lecture 9: What is a Surrogate key?

Lecture 10: Star Schema

Lecture 11: SnowFlake Schema

Lecture 12: Galaxy Schema or Fact Constellation Schema

Lecture 13: Differences between Star Schema and SnowFlake Schema?

Lecture 14: Conformed Dimension

Lecture 15: Junk Dimension

Lecture 16: Degenerate Dimension

Lecture 17: Slowly Changing Dimensions – Intro and Example Creation

Lecture 18: Slowly Changing Dimensions – Type 1, 2 and 3

Lecture 19: Slowly Changing Dimensions – Summary

Lecture 20: Step by Step approach to set up the Dimensional Model using a retail case study

Lecture 21: ER Model Vs Dimensional Model

Chapter 12: DWH Indexes

Lecture 1: What is an Index?

Lecture 2: Bitmap Index

Lecture 3: B-Tree index

Lecture 4: Bitmap Index Vs B Tree Index

Chapter 13: Data Integration and ETL

Lecture 1: What is Data Integration?

Lecture 2: What is ETL?

Lecture 3: Common Questions and Summary

Chapter 14: ETL Vs ELT

Lecture 1: ETL – Explained

Lecture 2: ELT – Explained

Instructors

Sid Inf
Data/ETL Architect

Rating Distribution

1 stars: 91 votes

2 stars: 164 votes

3 stars: 551 votes

4 stars: 1098 votes

5 stars: 915 votes

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