Database Questions

Question

1.     Discuss some applications of active databases.

2.     Discuss how time is represented in temporal databases and compare the different time dimensions. 

3.     What are the differences between valid time, transaction time, and bitemporal relations?

4.     Describe how the insert, delete, and update commands should be implemented on a valid time relation. 

5.     Describe how the insert, delete, and update commands should be implemented on a bitemporal relation.

6.     Describe how the insert, delete, and update commands should be implemented on a transaction time relation.

7.     What are the different phases of the knowledge discovery from databases! Describe a complete application scenario in which new knowledge may be mined from an existing database of transactions

8.     What are the goals or tasks that data mining attempts to facilitate?

9.     What are the five types of knowledge produced from data mining? 

10.  What are classification rules and how are decision trees related to them?

11.  How does clustering differ from classification?

12.  What is a data warehouse? How does it differ from a database? 

13.  Define the terms: OLAP (Online Analytical Processing), ROLAP (Relational 

14.  Describe the characteristics of a data warehouse. Divide them into functionality 

15.  What is the multidimensional data model? How is it used in data warehousing? 

16.  Define these terms: Star Schema, Snowflake Schema, Fact Constellation, Data Marts. 

17.  What types of indexes are built for a warehouse? Illustrate the uses for each with 

18.  Describe the steps of building a warehouse. 

19.  What considerations playa major role in the design of a warehouse? 

20.  List the open issues and research problems in data warehousing. 

21.  List the difficulties in implementing a data warehouse. 

22.  Discuss what is meant by each of the following terms: database authorization, access control, data encryption, privileged (system) account, database audit, audit trail.

23.  Discuss the types of privileges at the account level and those at the relation level. 

24.  How is the view mechanism used as an authorization mechanism? 

1. List the types of privileges available in SQL. 
2. What is the difference between discretionary and mandatoryaccess control? 
3. What are the typical security classifications? Discuss the simple security property and the *-property, and explain the justification behind these rules for enforcing multilevel security. 
4. What is a statistical database? Discuss the problem of statistical database security. 
5. How is privacy related to statistical database security? What meaures can be taken  to ensure some degree of privacy in statistical databases? 
6. What is flow control as a security measure? What types of flow control exist? 

31.  What is the goal of encryption? What process is involved in encrypting data and then recovering it at the other end?

32.  What is the public key infrastructure scheme? How does it provide security? 

33.  What are the different types of SQL injection attacks?

34.  How can privacy of data be preserved in a database?

Answer 1

1. Automation - such as auto-scheduled processes that start whenever the event occurs. An event occurs when conditions leading to the event become true. Example: WHEN a record with attribute A.value == RARE_VALUE and another record with attribute B.value = COMMON_VALUE happen, then event E1 has occurred. Event E1 initiates Activity A1. Separately, when A1 has run x number of times, Process P1 starts as a regularly scheduled process.
2. Qs 2-- 6 : Temporal Databases : I'm not interested in them at the present time;

Q 7:  Data cleaning -

First step in the Knowledge Discovery Process is Data cleaning in which noise and inconsistent data is removed.

2 Data Integration -

Second step is Data Integration in which multiple data sources are combined.

3 Data Selection -

Next step is Data Selection in which data relevant to the analysis task are retrieved from the database.

4 Data Transformation -

In Data Transformation, data are transformed into forms appropriate for mining by performing summary or aggregation operations.

5 Data Mining -

In Data Mining, data mining methods (algorithms) are applied in order to extract data patterns.

6 Pattern Evaluation -

In Pattern Evaluation, data patterns are identified based on some interesting measures.

7 Knowledge Presentation -

In Knowledge Presentation, knowledge is represented to user using many knowledge representation techniques.