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Learn Data Warehousing in 24 Hours

Unlike popular belief, Data Warehouse is not a single tool but a collection of software tools. A data warehouse will collect data from diverse sources into a single database. Using Business Intelligence tools, meaningful insights are drawn from this data.

The best thing about “Learn Data Warehousing in 1 Day" is that it is small and can be completed in a day. With this e-book, you will be enough knowledge to contribute and participate in a Data warehouse implementation project.

The book covers upcoming and promising technologies like Data Lakes, Data Mart, ELT (Extract Load Transform) amongst others. Following are detailed topics included in the book

Table content

Chapter 1: What Is Data Warehouse?

What is Data Warehouse?

Types of Data Warehouse

Who needs Data warehouse?

Why We Need Data Warehouse?

Data Warehouse Tools

Chapter 2: Data Warehouse Architecture

Characteristics of Data warehouse

Data Warehouse Architectures

Datawarehouse Components

Query Tools

Chapter 3: ETL Process

What is ETL?

Why do you need ETL?

ETL Process

ETL tools

Chapter 4: ETL Vs ELT

What is ETL?

Difference between ETL vs. ELT

Chapter 5: Data Modeling

What is Data Modelling?

Types of Data Models

Characteristics of a physical data model

Chapter 6: OLAP

What is Online Analytical Processing?

Types of OLAP systems

Advantages and Disadvantages of OLAP

Chapter 7: Multidimensional Olap (MOLAP)

What is MOLAP?

MOLAP Architecture

MOLAP Tools

Chapter 8: OLAP Vs OLTP

What is the meaning of OLAP?

What is the meaning of OLTP?

Difference between OLTP and OLAP

Chapter 9: Dimensional Modeling

What is Dimensional Model?

Elements of Dimensional Data Model

Attributes

Difference between Dimension table vs. Fact table

Steps of Dimensional Modelling

Rules for Dimensional Modelling

Chapter 10: Star and SnowFlake Schema

What is Multidimensional schemas?

What is a Star Schema?

What is a Snowflake Schema?

Difference between Start Schema and Snowflake

Chapter 11: Data Mart

What is Data Mart?

Type of Data Mart

Steps in Implementing a Datamart

Chapter 12: Data Mart Vs Data Warehouse

What is Data Warehouse?

What is Data Mart?

Differences between a Data Warehouse and a Data Mart

Chapter 13: Data Lake

What is Data Lake?

Data Lake Architecture

Key Data Lake Concepts

Maturity stages of Data Lake

Chapter 14: Data Lake Vs Data Warehouse

What is Data Warehouse?

What is Data Lake?

Key Difference between the Data Lake and Data Warehouse

Chapter 15: What Is Business Intelligence?

What is Business Intelligence

Why is BI important?

How Business Intelligence systems are implemented?

Four types of BI users

Chapter 16: Data Mining

What is Data Mining?

Types of Data

Data Mining Process

Modelling


Kirjailija:

  • Alex Nordeen

Muoto:

  • E-kirja

Kesto:

  • 102 sivut

Kieli:

englanti

Kategoriat:

  • Tieto
  • Tietokoneet ja IT

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