Implementing a Data Warehouse with SQL Server 2022

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2:36:09

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01 - Introduction

01 - Storing information in a data warehouse.mp4

00:50

02 - What you should know.mp4

00:37

03 - Set up the example databases.mp4

03:44

02 - 1. Data Warehouse Foundations

04 - Data warehouse core concepts.mp4

04:44

05 - Transactional DBs vs. data warehouses.mp4

06:07

06 - Dimensions and facts.mp4

08:07

07 - Star and snowflake schemas.mp4

03:30

08 - Hardware and infrastructure.mp4

03:13

03 - 2. Create a Data Warehouse

09 - Create a data warehouse in SQL Server.mp4

06:58

10 - Design dimension tables.mp4

07:04

11 - Design fact tables.mp4

04:08

12 - Create an indexed view.mp4

03:46

04 - 3. Columnstore Indexes

13 - Advantages of columnstore indexes.mp4

04:53

14 - Memory-optimized columnstore table.mp4

03:46

15 - Rebuild columnstore indexes.mp4

02:57

05 - 4. Extract, Transform, and Load

16 - What are ETL and SSIS.mp4

03:39

17 - Understand data flow.mp4

04:18

18 - Establish control flow.mp4

02:31

06 - 5. Implement an Azure Synapse Analytics Dedicated SQL Pool

19 - Hosting a DW in the cloud.mp4

06:02

20 - Create a dedicated SQL Pool.mp4

04:02

21 - Reserve resources with workload isolation groups.mp4

06:02

22 - Classify workloads.mp4

05:25

23 - Load data into a staging table.mp4

04:40

24 - Pause and remove resources in Azure.mp4

02:20

07 - 6. Enforce Data Quality

25 - SQL Server Data Quality Services.mp4

04:49

26 - Cleanse data with DQS.mp4

08:36

27 - Create a custom knowledge base.mp4

07:53

08 - 7. Master Data Services

28 - Introduction to Master Data Services.mp4

02:16

29 - Install MDS and IIS.mp4

05:12

30 - Configure Master Data Services.mp4

04:41

31 - Deploy a sample MDS model.mp4

06:51

32 - Install the MDS Excel add-in.mp4

02:29

33 - Update master data in Excel.mp4

04:22

09 - 8. Consume Data from the Warehouse

34 - Business intelligence applications.mp4

04:17

10 - Conclusion

35 - Next steps.mp4

01:20

Description

Data warehouses solve fundamentally different problems than a traditional transactional database, and SQL Server Data Warehouses provide a different model for storing valuable data. In this course, database expert Adam Wilbert guides you through the process of developing data warehouses in SQL Server 2022 to provide a robust, trustworthy platform to serve all your business intelligence reporting and analysis workloads. Explore data warehouse foundations, then get started creating a data warehouse in SQL Server. Learn about columnstore indexes, as well as how to automate the tasks associated with integrating multiple data sources together into a warehouse. Find out how to implement an Azure Synapse Analytics Dedicated SQL Pool and enforce data quality using Data Quality Services. Discover ways to use Master Data Services, plus learn how to consume data from your warehouse with business intelligence applications.

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