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Data Warehouse basics for absolute beginners in 30 mins
Rating: 4.5 out of 5(1,479 ratings)
18,752 students

Data Warehouse basics for absolute beginners in 30 mins

Data Warehouse basic concepts like architecture, dimensional modeling, fact vs dimension table, star vs snowflake schema
Created byEshant Garg | | LearnCloud.Info | 100,000+ Enrollments
Last updated 7/2021
English
English [Auto],

What you'll learn

  • Data Warehouse Basic concepts
  • Dimensional modeling
  • Facts and Dimensional tables
  • Schema and Snowflake schema

Course content

1 section • 13 lectures • 34m total length

  • Is this course good for me? Set expectation0:27
  • Introduction1:30

    Explore data warehouses, learn why we need them, and how they differ from transactional databases, along with dimensional modeling, facts and dimensions, and star and snowflake schemas.

  • What is Data Warehouse1:35

    Explore what a data warehouse is, how it collects data from multiple software systems, uses extract, transform, and load, and stores integrated data for reports and data mining.

  • Why we need Data Warehouse?2:48

    Explain why a data warehouse is needed to provide easy access to data for decision-making, ensure consistent reporting of key indicators, and support a data-driven culture that enables faster growth.

  • Ideal Data Warehouse Solution3:39

    Translate business problems into accessible data warehouse requirements for simple slicing and dicing, enabling fast, consistent analytics with trusted data and clear business vocabulary.

  • Responsibility of Data Warehouse designer2:04

    Define the data warehouse designer's responsibilities by identifying business users, creating personas, and tailoring data presentation to support accurate decisions with relevant, trustworthy data and simple interfaces.

  • SQL Server (OLTP) vs Data Warehouse (OLAP)2:26

    Compare online transaction processing (OLTP) with online analytical processing (OLAP) to contrast high-volume transactions, current non-volatile data, and detailed versus summarized data in a data warehouse at scale.

  • Dimensional Modeling5:16

    Discover the dimensional model, a simple, user-friendly data warehouse design that uses facts and dimensions for fast, understandable analytics. See how overnight ETL delivers fresh data in a star-shaped schema.

  • Facts and Fact Table6:14

    Explore the role of facts and fact tables in a data warehouse, including additive measures, foreign keys to dimensions, and time dimensions for transaction analysis.

  • Dimensions and Dimension table3:41

    Explore how dimension tables provide descriptive context for a business event, answering who, what, where, when, how, and why, and how product attributes populate a rich dimension for analysis.

  • Star vs Snowflake3:03

    The star schema presents a clean, simple structure where each dimension links to the fact table for easy, recognizable analysis, while the snowflake schema extends normalization with multiple dimension tables.

  • Summary1:16

    Review data warehouse fundamentals, compare OLTP and OLAP, and explain dimensional modeling with facts and dimensions, including Ishtar and snowflake schema.

  • Bonus Lecture0:41

Requirements

  • Basic Database Understanding

Description

Important Note:

Please note that this is NOT a full course but a single module of the full-length course, and intended to cover very basic fundamental concepts for absolute beginners so that they can speed up with Azure Synapse SQL Data Warehouse course.

This module is NOT GOOD for you if:

  • You are already experienced in this technology

  • You are looking for an intermediate or advance concepts

  • You are looking for practical examples or demo

This module is GOOD for you if:

  • You want to understand the basic fundamental concepts of this technology.

This is a free module to help others. If you are not in the intended audience, I request you to please feel free to unenroll.

Where I can find a full-length course?

Please look at the bonus lecture in the end.


What will students learn in this course?

  • Microsoft SQL Data Warehouse (Crash course to speed up with Cloud warehousing)

Level

  • Beginners

Intended Audience

  • Anyone who wants to start learning Data warehousing

Language

  • English

  • If you are not comfortable in English, please do not take the course, captions are not good enough to understand the course.

Target Students

  • Database and BI developers

  • Database Administrators

  • Data Analyst or similar profiles

Prerequisites

  • Basic T-SQL and Database concepts


Course In Detail

Data Warehouse Crash Course

  • In this module, you will learn, what is Data Warehouse, Why we need it and how it is different from the traditional transactional database.

  • We will learn the concept of dimensional modeling which is a database design method optimized for data warehouse solutions.

  • Then I will explain what we mean when we say facts and their corresponding fact tables. What are the dimensions and their corresponding dimension tables?

  • how are these special kinds of tables joined together to form a star schema or snowflake schema?

  • This section will establish the foundation before you start my course on Azure Synapse Analytics or formally known as Azure SQL Data Warehouse.


[Tags]

Microsoft SQL Server, Azure SQL Server, Azure SQL Data Warehouse, Data Factory, Data Lake, Azure Storage, Azure Synapse Analytics Service, PolyBase, Azure monitoring, Azure Security, Data Warehouse, SSIS

Who this course is for:

  • Database Developer
  • College Students
  • Data Analyst or similar profiles
  • Anyone interested to learn Basic Data Warehousing concept

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