Learn Data Warehousing in 24 Hours

Alex Nordeen

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Beschreibung zu „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


Verlag:

PublishDrive

Veröffentlicht:

2021

Druckseiten:

ca. 73

Sprache:

English

Medientyp:

eBook


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