Data Warehouse Essential: Concepts
Data Warehouse
| Beginner
- 18 videos | 1h 43m 3s
- Includes Assessment
- Earns a Badge
Discover the fundamentals of data warehousing and the approaches of implementing it. Explore Data Warehouse planning, processes, schemes, and terms. You will also examine global and local Data Warehouses as well as comparing Data Warehouses with RDBMS and Data Lake.
WHAT YOU WILL LEARN
-
identify the characteristics of strategic information and the need for data warehousing to manage strategic information
list the essential differences between OLAP and data warehousing capabilities
specify the essential guidelines that should be followed in order to implement a successful data warehouse project on the cloud and on-premise
compare essential on-premise and on-cloud data warehousing products and components
identify the essential characteristics of data warehouse projects
compare normalization and denormalization processes in data warehouse projects
compare the contrasting features of OLTP and data warehouse from the perspective of indexes, joins, data duplication, and data aggregation
differentiate global data warehouse from local data warehouse, and recognize critical features, capabilities, and implementation
recall essential data warehouse terms that are frequently used when implementing data warehouse projects -
recall important data warehouse processes that are generally applied to facilitate business intelligence, including the essential ETL processes
recall how the ER schemas are implemented in data warehouse projects
specify how the star schemas are implemented in data warehouse projects
describe how the snowflake schemas are implemented in data warehouse projects
identify the critical capabilities of multi-valued dimensions and the essential comparison between weighted and impact reports
illustrate the architectural concept of reporting and classify the various essential types of reports
compare data warehouse, RDBM, data lake and their implementation scenarios
compare the critical features, capabilities, and the implementation scenarios of Azure and AWS data lakes
identify how to implement and facilitate data warehouse given a scenario
IN THIS COURSE
-
8m 28s
-
7m 2s
-
3. Planning Data Warehouse Implementation Part 19m 8s
-
4. Planning Data Warehouse Implementation Part 24m 5s
-
5. Characteristics of Data Warehouse Projects Part 16m 45s
-
6. Characteristics of Data Warehouse Projects Part 26m 14s
-
7. Technical Comparison of OLTP and Data Warehouse6m 16s
-
8. Global and Local Data Warehouses3m 37s
-
9. Data Warehouse Terms4m 45s
-
10. Data Warehouse Processes9m 19s
-
11. Data Warehouse Schemas - ER4m 3s
-
12. Data Warehouse Schemas - Star4m 32s
-
13. Data Warehouse Schemas - Snowflake3m 38s
-
14. Multi-Valued Dimension and Report Types4m 42s
-
15. Analytical Reports5m 3s
-
16. Comparing Data Warehouse with RDBMS and Data Lake6m 59s
-
17. Comparing Azure and AWS Data Lakes4m 58s
-
18. Exercise: Implementing Data Warehouse3m 31s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.
