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Data Warehouse Course: Basic to Advanced Concepts

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Data Warehouse Course: Basic to Advanced Concepts

Data Warehouse Concepts: Learn the BI/Data Warehouse/BIG DATA Concepts from scratch and become an expert.

updated on icon Updated on Jun, 2025

language icon Language - English

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English [CC]

category icon Development ,Data Science,Data Analysis

Lectures -120

Duration -6.5 hours

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Course Description

You will study all the terms and ideas linked to the Data Warehouse in this course, including OLTP, OLAP, Dimensions, Facts, and many more, as well as other concepts associated with it, such as what Start Schema and Snowflake Schema imply, as well as other alternatives and their distinctions.

Data Warehouse: Basic to Advanced Concepts Overview

Data Warehouse: Basic to Advanced Concepts Course will help you understand facts, dimensions, aggregations, and frequently employed ETL approaches. Additionally, it describes how the Data Warehouse manages data and how to read and write data into the Warehouse.

After finishing this course, you will have a solid understanding of all the Data Warehouse principles, which should be enough to set you on the path to becoming an ETL developer or administering the Data Warehouse environment with the aid of various tools.

Why Learn Data Warehouse?

There are many reasons why you should learn data warehouse. Here are some of the most important ones:

  • Data warehouses are essential for businesses of all sizes. They provide a centralized repository for data, which can be used to make better decisions, improve operations, and drive innovation.

  • Learning data warehouse can help you develop valuable skills in data analysis and business intelligence. These skills are in high demand and can lead to lucrative careers in the tech industry.

  • Data warehouse is a complex subject, but it is also very rewarding. By learning data warehouse, you will gain a deep understanding of how data is stored, managed, and analyzed. This knowledge can be used to solve real-world problems and make a positive impact on the world.

Goals

  • Brief about the Data Warehouse and how the concept came into existence

  • Business Intelligence Concepts

  • Data Warehouse Architectures

  • ODS - Operational Data Store

  • OLAP - Online Analytical Processing

  • Data Marts

  • Metadata

  • Data Modeling

  • Entity Relationship Model

  • Dimensional Model

  • Data Integration & ETL

  • ETL vs ELT

  • ETL - Extraction Transformation & Loading

  • Typical Roles in a Data Warehouse Project

  • DW/BI/ETL Implementation Approach

Prerequisites

  • Basic understanding of the IT (Software) industry.

  • Familiar with the basic concept of Database/RDBMS.

Data Warehouse Course: Basic to Advanced Concepts

Curriculum

Check out the detailed breakdown of what’s inside the course

Brief about the Data warehouse

4 Lectures
  • play icon Is Data Warehouse still relevant in the age of Big Data? 04:25 04:25
  • play icon Why do we need a Data Warehouse? 05:26 05:26
  • play icon What is a Data Warehouse? 05:48 05:48
  • play icon Characteristics of a Data Warehouse 05:43 05:43

Business Intelligence

4 Lectures
Tutorialspoint

Data Warehouse Architectures

8 Lectures
Tutorialspoint

ODS - Operational Data Store

4 Lectures
Tutorialspoint

OLAP

7 Lectures
Tutorialspoint

Data Mart

6 Lectures
Tutorialspoint

Metadata

6 Lectures
Tutorialspoint

Data Modeling

2 Lectures
Tutorialspoint

Entity Relational Data Model

14 Lectures
Tutorialspoint

Dimensional Model

21 Lectures
Tutorialspoint

DWH Indexes

4 Lectures
Tutorialspoint

Data Integration and ETL

3 Lectures
Tutorialspoint

ETL Vs ELT

3 Lectures
Tutorialspoint

ETL - Extraction Transformation & Loading

3 Lectures
Tutorialspoint

Typical Roles In DWH Project

13 Lectures
Tutorialspoint

DW/BI/ETL Implementation Approach

18 Lectures
Tutorialspoint

Instructor Details

Inf Sid

Inf Sid

Business Intelligence Consultant and Trainer with 14+ years of extensive work experience on various client engagements. Delivered many large data warehousing projects and trained numerous professionals on business intelligence technologies. Extensively worked on all facets of data warehousing including requirement gathering, gap analysis, database design, data integration, data modeling, enterprise reporting, data analytics, data quality, data visualization, OLAP.

Has worked on broad range of business verticals and hold exceptional expertise on  various ETL tools like Informatica Power center, SSIS, ODI and IDQ, Data Virtualization, DVO, MDM.

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