Designing a Data Warehouse
Bluelime Learning Solutions
1:51:36
Description
Learn how to design a Microsoft SQL Server Data Warehouse
What You'll Learn?
- Setup Microsoft SQL Server
- Configure database settings for data warehousing
- Enable SQL Server Agent
- Logical design of data warehouse
- Physical design of data warehouse
- Design Dimension Tables
Who is this for?
What You Need to Know?
More details
DescriptionA data warehouse is a central repository of information that can be analysed to make more informed decisions. Data flows into a data warehouse from transactional systems, relational databases, and other sources, typically on a regular cadence. Business analysts, data engineers, data scientists, and decision makers access the data through business intelligence (BI) tools, SQL clients, and other analytics applications.
Data and analytics have become indispensable to businesses to stay competitive. Business users rely on reports, dashboards, and analytics tools to extract insights from their data, monitor business performance, and support decision making. Data warehouses power these reports, dashboards, and analytics tools by storing data efficiently to minimize the input and output (I/O) of data and deliver query results quickly to hundreds and thousands of users concurrently.
A data warehouse is specially designed for data analytics, which involves reading large amounts of data to understand relationships and trends across the data. A database is used to capture and store data, such as recording details of a transaction.
This course explains the design of dimension tables, physical and logical design of a data warehouse .
Physical design is the creation of the database with SQL statements. During the physical design process, you convert the data gathered during the logical design phase into a description of the physical database structure. Physical design decisions are mainly driven by query performance and database maintenance aspects.
The process of logical design involves arranging data into a series of logical relationships called entities and attributes. An entity represents a chunk of information. In relational databases, an entity often maps to a table. An attribute is a component of an entity that helps define the uniqueness of the entity.
A dimension table is a table in a star schema of a data warehouse. A dimension table stores attributes, or dimensions, that describe the objects in a fact table. In data warehousing, a dimension is a collection of reference information about a measurable event.
Who this course is for:
- Beginners to data warehouse
- Beginner Data Analyst
- Beginner Data Scientist
A data warehouse is a central repository of information that can be analysed to make more informed decisions. Data flows into a data warehouse from transactional systems, relational databases, and other sources, typically on a regular cadence. Business analysts, data engineers, data scientists, and decision makers access the data through business intelligence (BI) tools, SQL clients, and other analytics applications.
Data and analytics have become indispensable to businesses to stay competitive. Business users rely on reports, dashboards, and analytics tools to extract insights from their data, monitor business performance, and support decision making. Data warehouses power these reports, dashboards, and analytics tools by storing data efficiently to minimize the input and output (I/O) of data and deliver query results quickly to hundreds and thousands of users concurrently.
A data warehouse is specially designed for data analytics, which involves reading large amounts of data to understand relationships and trends across the data. A database is used to capture and store data, such as recording details of a transaction.
This course explains the design of dimension tables, physical and logical design of a data warehouse .
Physical design is the creation of the database with SQL statements. During the physical design process, you convert the data gathered during the logical design phase into a description of the physical database structure. Physical design decisions are mainly driven by query performance and database maintenance aspects.
The process of logical design involves arranging data into a series of logical relationships called entities and attributes. An entity represents a chunk of information. In relational databases, an entity often maps to a table. An attribute is a component of an entity that helps define the uniqueness of the entity.
A dimension table is a table in a star schema of a data warehouse. A dimension table stores attributes, or dimensions, that describe the objects in a fact table. In data warehousing, a dimension is a collection of reference information about a measurable event.
Who this course is for:
- Beginners to data warehouse
- Beginner Data Analyst
- Beginner Data Scientist
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Udemy
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- Training sessions 19
- duration 1:51:36
- English subtitles has
- Release Date 2024/01/31
