Frequently Asked Questions in Datawarehouse - Concepts

Beginners
1. What is a Data Warehouse?
2. What is a DataMart?
3. What is Data Mining?
4. What do you mean by Dimension Attributes?
5. What is the difference between a data warehouse and a data mart?
6. What is the difference between OLAP, ROLAP, MOLAP and HOLAP?
7. What is a star schema?
8. What does it mean by grain of the star schema?
9. What is a snowflake schema?
10. What is a surrogate key?
11. What oracle tools are available to design and build a data warehosue/data mart?
12. What is a Cube?
13. What does ETL stand for?
14. What is Aggregation?
15. what is Business Intelligence?
16. What is transitive dependency?
17. what is the current version of informatica?
18. What are the tools in informatica?Why we are using that tools?
19. What is a transformation?
20. What is a mapping?
21. what is fact less fact table?
22. What is a Schema?
23. What is A Context?
24. What is a Bomain key?
Advanced
25. Who are the Data Stewards and whats their role?
26. What are the most important features of a data warehouse?
27. What the easiest way to build a corporate specific time dimension?
28. What is a Real-Time Data Warehouse - RTDW?
29. What is Slowly Changing Dimension?
30. What is a Conformed Dimension?
31. What is TL9000?

Add a FAQ


Beginners
1. What is a Data Warehouse?






2. What is a DataMart?






3. What is Data Mining?






4. What do you mean by Dimension Attributes?






5. What is the difference between a data warehouse and a data mart?






6. What is the difference between OLAP, ROLAP, MOLAP and HOLAP?






7. What is a star schema?






8. What does it mean by grain of the star schema?






9. What is a snowflake schema?






10. What is a surrogate key?






11. What oracle tools are available to design and build a data warehosue/data mart?






12. What is a Cube?






13. What does ETL stand for?






14. What is Aggregation?






15. what is Business Intelligence?






16. What is transitive dependency?






17. what is the current version of informatica?






18. What are the tools in informatica?Why we are using that tools?






19. What is a transformation?






20. What is a mapping?






21. what is fact less fact table?






22. What is a Schema?






23. What is A Context?






24. What is a Bomain key?






Advanced
25. Who are the Data Stewards and whats their role?






26. What are the most important features of a data warehouse?






27. What the easiest way to build a corporate specific time dimension?






28. What is a Real-Time Data Warehouse - RTDW?






29. What is Slowly Changing Dimension?






30. What is a Conformed Dimension?






31. What is TL9000?













What kinds of data belong in a data warehouse?
Data that comes from your mainframe or client/server computing systems, data that you use to manage your business, or any type of data that has value to your business. The idea behind the data warehouse is to capture all types of data into a central location. Once this is done you have the ability to link different types of data together and turn that data into valuable information that can be used for your business needs, analysis, discovery and planning.
Why would I want to access the data warehouse when I have a mainframe computing system?
Your computing system is set up to handle subject specific day to day business and transaction processing, such as payroll or course registration. The reports created in this type of system are specific to the subject matter. The benefits to putting your data into the data warehouse include:
 Merging subject specific data together to create information
 Standardizing data across the University
 Improving turnaround time for reporting
 Lowering costs because you can produce your own reports instead of costly, centrally printed and distributed mainframe reports
 Sharing data or allowing others to easily access your data will free staff from the tasks of extracting data and reporting for other departments or colleges
What's metadata? What's a data dictionary?
Metadata is data about data. Metadata gives you data element definitions, data layouts, and information about the data element's location. Data elements are the smallest unit of data that can be described, for example the zip code field within an address database record. The University's data warehouse refers to their metadata as data dictionaries. You can access the data dictionaries on the IDEA web page . Click on the Information button, then click on the Data Element Dictionary for the database of your choice.