Data modeling interview FAQs list

 

1. what are 3 levels of Data modeling 
1. Conceptual 
2. logical
3. physical model
   
2. Types of Fact tables 
1. 
   
3. Logical and physical model - Differences ?
4. Star schema & Snowflake schema - Differences ?
5. Granularity and Granule
6. Types of Dimension tables
7. What is factless fact table
8. What is Data Mart
9. Steps in Datawarehouse life cycle steps
   
   
10. ERWIN qsns
1. Erwin - Data modeler workspace
2. Erwin - Domains
3. Erwin - types of relationships
4. Erwin - indexes how
5. Erwin - Forward and reverse engineering steps
6. Erwin - Complete compare feature
7. Erwin - Naming standards
8. Erwin - Name hardening
9. Erwin - querying tool
10. Erwin - subject areas
11. Erwin - identifying and non identifying relationships differences
11. Fact and dimension table - differences
12. What is Datawarehouse
13. what is ODS( operational data store)
14.  OLTP & OLAP- differences (pg 17) 53
15. What are SQL performance tuning measures & tips
16. what are bottlenecks which effects database performance
17. how do you tune a query using explain plan
18. what is summary advisor
19. what is most likely reason that sql query may run slowly
20. what is latch free event
21. what is proactive tuning and reactive tuning
22. what is Rule based optimiser and cost based optimizer
23. list Perf tuning enhancements in oracle
24. how do you confirm that table has disproportionate fragmentation
25. what can you do to optimize %xyz" queries 
26. where does input output statistics of table exist in oracle
27. when is right time to rebuiled index
28. what information does STATSPACK report give 
29.  redo,rollback , undo- differences
30. Aggregate and summarized tables  - differences
31. what operations can be done on OLAP cube
32. data quality checks -pg 28
33. types of indexes 53
34. types of fact tables 51
35. types of dimension tables(30, 46,48)
36. surrogate key (33)
37. Normalization (34)
38. sql query : find nth highest salary - 54
39. sql query : find and delete duplicate rows
40. What are roles of data modeler 61
41. Most common KPI list 
42. Which Data profiling tools did you use
1. Informatica data profiling
2. Open source data quality profiling
43.