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Learn MoreData Warehousing
Rating: 3.3 out of 53.3(194 ratings)
1,195 students
Data Warehousing
An introductory course about understanding data warehousing, its architecture, flow, applications and modeling.
Created byThe Art Of Service
Last updated 3/2015
English
What you'll learn
- Be introduced to the data warehouse, its advantages and disadvantages.
- Know the concepts, lifecycle and rules of the data warehouse.
- Be informed of the importance and the techniques of data warehouse modeling.
- Recognize the different applications of data warehousing.
- Look forward to the future of the data warehouse.
Explore related topics
Course content
9 sections • 65 lectures • 2h 48m total length
- Introduction and Objectives0:30
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
Section Outline
Lecture 2: Definition of Data Warehousing
Lecture 3: History of Data Warehousing
Lecture 4: Advantages of Data Warehousing
Lecture 5: Disadvantages of Data Warehousing
Lecture 6: Benefits of Data Warehousing
Lecture 7: Concepts of Data Warehousing - Definition of Data Warehousing4:11
This lecture will explain the definitions of data warehousing.
- History of Data Warehousing4:47
This lecture will talk about the history and relevance of data warehousing.
- Advantages of Data Warehousing2:23
This lecture will identify the different advantages of data warehousing.
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Lecture outline:
0:00 Introduction to the Advantages of Data Warehousing
0:21 Main Advantages of Data Warehousing
1:15 Powerful Feature of Data Warehousing
- Disadvantages of Data Warehousing3:08
This lecture will identify the different disadvantages of data warehousing.
- Benefits of Data Warehousing2:11
This lecture will identify the different benefits of data warehousing.
- Concepts of Data Warehousing4:10
This lecture will identify and explain the concepts of data warehousing.
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Lecture outline:
0:00 Introduction to the Concepts of Data Warehousing
0:06 Subject Oriented
1:00 Integrated
1:52 Time Variant
3:13 Non Volatile
- Introduction and Objectives0:37
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
Section Outline
Lecture 10: Online Transaction Processing
Lecture 11: Data Store
Lecture 12: Data Mart
Lecture 13: Design Schemas
Lecture 14: Meta Data
Lecture 15: Data Webhouse and Data Warehouse QueriesLecture 16: Extract, Transform, Load
- Online Transaction Processing8:42
This lecture will identify the difference between online transaction processing or OLTP and online analytical processing or OLAP.
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Lecture outline:
0:00 Online Transaction Processing
1:12 Advantages of OLTP
1:49 Disadvantages of OLTP
2:40 Online Analytical Processing
3:48 OLAP Tools
5:11 Types of OLAP Systems
- Data Store0:53
This lecture will explain the definition of data store and some reasons for creating it.
- Data Mart3:24
This lecture will explain data mart and identify its characteristics.
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Lecture outline:
0:00 Definition of Data Mart
1:23 Primary Use of Data Mart
2:24 Characteristics of Data Mart
2:42 Reasons for Creating Data Mart
- Design Schemas7:58
This discussion will focus on design schemas namely Star schema and Snowflake schema.
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Lecture outline:
0:00 Star Schema
0:38 Model of Star Schema
1:30 Components of Star Schema
2:54 Advantages of Star Schema
4:21 Disadvantages of Star Schema
4:54 Snowflake Schema
5:52 Common Uses of Snowflake Schema
6:54 Advantages of Snowflake Schema
7:24 Disadvantages of Snowflake Schema
- Meta Data3:19
This lecture will talk about metadata and its components.
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Lecture outline:
0:00 Definition of Meta Data
2:40 Components of Meta Data
- Data Webhouse and Data Warehousing Queries0:51
This lecture will identify the difference between data webhouse and data warehouse queries.
- Extract, Transform, Load6:55
This lecture will discuss a process in database usage namely Extract, Transform, and Load or ETL.
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Lecture outline:
0:00 ETL Defined
0:29 Extract
0:57 ETL Architecture Pattern
2:30 Transform
2:53 Transformation Types
4:15 Load
- Introduction and Objectives0:25
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
Section Outline
Lecture 19: Data Warehouse Lifecycle
Lecture 20: Design
Lecture 21: Prototype
Lecture 22: Deploy
Lecture 23: Operate
Lecture 24: EnhanceLecture 25: Data Warehouse Cycle of Cycles
Lecture 26: First Loop
Lecture 27: Second Loop
Lecture 28: Third Loop
Lecture 29: Fourth Loop
Lecture 30: Related FactorsLecture 31: Rules of Data Warehouse
- Data Warehouse Lifecycle0:36
This lecture will talk about the data warehouse lifecycle and its major phases.
- Design1:05
This discussion will focus on a major phase in the data warehouse lifecycle, namely the design phase.
- Prototype1:00
This discussion will focus on a major phase in the data warehouse lifecycle, namely the prototype phase.
- Deploy1:16
This discussion will focus on a major phase in the data warehouse lifecycle, namely the deploy phase.
- Operate0:30
This discussion will focus on a major phase in the data warehouse lifecycle, namely the operate phase.
- Enhance0:34
This discussion will focus on a major phase in the data warehouse lifecycle, namely the enhance phase.
- Data Warehouse Cycle of Cycles0:30
This discussion will center on another cycle that happens in the lifecycle, hence the data warehouse cycle of cycles.
- First Loop0:38
This lecture will identify the first loop involved in the cycle of cycles.
- Second Loop0:59
This lecture will identify the second loop involved in the cycle of cycles.
- Third Loop1:46
This lecture will identify the third loop involved in the cycle of cycles.
- Fourth Loop0:28
This lecture will identify the fourth loop involved in the cycle of cycles.
- Related Factors3:21
This lecture will explain some related factors in the data warehouse lifecycle process.
- Rules of Data Warehouse6:51
This lecture will identify and explain the rules in the data warehouse.
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Lecture outline:
0:00 Introduction to the Rules of Data Warehouse
0:47 Multi-Dimensional Conceptual View
1:15 Transparency
2:00 Accessibility
2:32 Consistent Reporting Performance
3:15 Client-Server Architecture
3:51 Generic Dimensionality
4:33 Dynamic Sparse Matrix Handling
4:55 Multi-User Support
5:16 Unrestricted Cross-Dimensional Operation
5:37 Intuitive Data Manipulation
5:58 Flexible Reporting
6:11 Unlimited Dimensions and Aggregation Levels
- Introduction and Objectives0:25
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
Section Outline
Lecture 34: Introduction to Data Warehouse Architecture
Lecture 35: Key Components
Lecture 36: Benefits of Data Warehouse Architecture
Lecture 37: Typical Architecture of Data Warehousing
Lecture 38: Common Architecture
Lecture 39: Data Warehouse Information Flow - Introduction to Data Warehouse Architecture0:41
This lecture will explain the data warehouse architecture.
- Key Components6:07
This lecture will discuss the key components involved in the data warehouse architecture.
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Lecture outline:
0:00 Introduction to the Key Components of Data Warehouse Architecture0:10 Data Architecture
1:59 Infrastructure Architecture
3:15 Technical Architecture
- Benefits of Data Warehouse Architecture1:18
This lecture will identify the different benefits of the data warehouse architecture.
- Typical Architecture of Data Warehousing6:32
This discussion will focus and explain the typical architecture of a data warehouse.
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Lecture outline:
0:00 Typical Architecture of a Data Warehouse
0:07 Operational Data Sources
0:36 Operational Data Store
1:08 Load Manager
1:28 Warehouse Manager
2:33 Query Manager
2:59 Detailed Data
3:19 Lightly and Highly Summarized Data
3:56 Archive / Backup Data
4:18 MetaData
5:39 End-User Access Tools
- Common Architecture2:45
This lecture will introduce and explain common architecture of data warehouses.
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Lecture outline:
0:00 Common Architectures
0:25 Data Warehouse Architecture: Basic
1:19 Data Warehouse Architecture: With a Staging Area1:59 Data Warehouse Architecture: With a Staging Area and Data Marts - Data Warehouse Information Flow0:43
This discussion will center on the information flow in a data warehouse architecture.
- Introduction and Objectives0:24
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
Section Outline
Lecture 42: Importance of Data Modeling
Lecture 43: Introduction to Data Modeling Techniques
Lecture 44: Entity-Relationship Modeling
Lecture 45: Limitations of ER
Lecture 46: Dimensional Modeling
Lecture 47: Benefits of Dimensional Modeling - Importance of Data Modeling3:17
This lecture will identify the importance of data modeling.
- Introduction to Data Modeling Techniques0:57
This lecture will introduce the different modeling techniques.
- Entity-Relationship Modeling7:22
This lecture will explain one of the modeling techniques, namely entity-relationship modeling.
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Lecture outline:
0:00 Definition of Entity-Relationship Modeling
0:32 Entity
2:15 Relationship
3:43 Attributes
5:37 Other Concepts
- Limitations of ER2:06
This lecture will identify the limitations of entity-relationship modeling.
- Dimensional Modeling4:10
This lecture will explain one of the modeling techniques, namely dimensional modeling.
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Lecture outline:
0:00 Definition of Dimensional Modeling
0:38 Basic Concepts of Dimensional Modeling
0:46 Fact
1:14 Measure
1:40 Dimension
2:48 Visualization
- Benefits of Dimensional Modeling2:07
This lecture will identify the benefits of dimensional modeling.
- Introduction and Objectives0:25
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
Section Outline
Lecture 50: Introduction to Data Warehouse Application
Lecture 51: Retail Industry
Lecture 52: Manufacturing and Distribution
Lecture 53: Bank
Lecture 54: Insurance Company
Lecture 55: Health Care ProvidersLecture 56: Government Agencies
Lecture 57: Internet Companies
Lecture 58: Telecommunications
Lecture 59: Sports - Introduction to Data Warehouse Application2:40
This lecture will introduce the different applications of data warehousing.
- Retail Industry3:34
This lecture will identify the different applications of data warehousing, specifically the retail industry.
- Manufacturing and Distribution3:01
This lecture will identify the different applications of data warehousing, specifically manufacturing and distribution.
- Bank1:47
This lecture will identify the different applications of data warehousing, specifically the banking industry.
- Insurance Company3:33
This lecture will identify the different applications of data warehousing, specifically the insurance companies.
- Health Care Providers5:15
This lecture will identify the different applications of data warehousing, specifically health care providers.
- Government Agencies3:15
This lecture will identify the different applications of data warehousing, specifically government agencies.
- Internet Companies3:27
This lecture will identify the different applications of data warehousing, specifically internet companies.
- Telecommunications3:58
This lecture will identify the different applications of data warehousing, specifically telecommunications.
- Sports0:58
This lecture will identify the different applications of data warehousing, specifically the sports industry.
- Introduction and Objectives0:25
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
Section Outline
Lecture 62: Challenges to Data Warehousing
Lecture 63: Ensuring Data Quality
Lecture 64: Ensuring Performance
Lecture 65: Testing the Data Warehouse
Lecture 66: Reconciliation of Data
Lecture 67: User AcceptanceLecture 68: Future of Data Warehouse
- Challenges to Data Warehousing0:44
This lecture will discuss some challenges in data warehousing.
- Ensuring Data Quality2:39
This lecture will identify a reason why data warehousing can become complex, namely ensuring data quality.
- Ensuring Performance3:05
This lecture will identify a reason why data warehousing can become complex, namely ensuring performance.
- Testing the Data Warehouse2:01
This lecture will identify a reason why data warehousing can become complex, namely testing the data warehouse.
- Reconciliation of Data1:59
This lecture will identify a reason why data warehousing can become complex, namely reconciliation of data.
- User Acceptance1:14
This lecture will identify a reason why data warehousing can become complex, namely user acceptance.
- Future of Data Warehouse10:33
This discussion will center on the future of data warehousing.
- Data Warehousing Glossary of Terms3:00
This e book is a list of terms and definitions often used in the field of data warehousing.
- Final Exam1:00
Now that you've finished your Udemy course, - you are eligible to sit your official Certification exam.
Certification is not mandatory.
Once you've completed the course, email our exam department at support@theartofservice.com to purchase your exam voucher and sit your final exam.Exam access includes more information to better prepare for the exam including a workbook, sample exam plus the final exam.
Please include the course name in your email for us to send the correct information.
Any questions please contact support@theartofservice.com
You will receive a PDF certificate through your email upon passing the examination. - Conclusion - Final Lecture1:27
A final message from our CEO.
Requirements
- Basic understanding of the IT industry
- Knowledge of the English language
Description
Discover the latest data storage trend implemented by leading IT Professionals around the globe, known as Data Warehousing.
A data warehouse (DW) is a database used for reporting. The data is uploaded from the operational systems and may pass through an operational data store for additional processes before it is used in the data warehouse for reporting. This introductory course will discuss its benefits and concepts, the twelve rules which should be followed, the lifecycle of data that is warehoused, the flow and the architecture of data warehouse. It will also teach learners the applications of data warehousing, its challenges and its future.
Who this course is for:
- Recent graduates looking to get a foothold in the IT Industry.
- Finance professionals wanting to learn about Data Warehouses for reporting and analysis purposes, businesses looking to update and improve on data storage, analysis, and reporting processes.
- IT professionals wanting to learn more about data storage, Data Warehousing modeling, or Data Warehousing applications.