AMIETE – IT (OLD SCHEME)

Code: AT19                                       Subject: DATA WAREHOUSING AND DATA MINING

Time: 3 Hours                                                                                                     Max. Marks: 100

NOTE: There are 9 Questions in all.

· Question 1 is compulsory and carries 20 marks. Answer to Q. 1. must be written in the space provided for it in the answer book supplied and nowhere else.

· Out of the remaining EIGHT Questions answer any FIVE Questions. Each question carries 16 marks.

· Any required data not explicitly given, may be suitably assumed and stated.

Q.1       Choose the correct or the best alternative in the following:                                 (2 10)

       a.      SKAT stands for

(A) Systematic Knot adding Technology.

(B) Symbolic Knowledge Acquisition Technology.

(C) Systematic Knowledge Acquisition Technology.

(D) System Knowledge And Technology.

       b.     Partitioning of data refers to

(A) Breakup of data.                              

               (B) Separating physical units.

(C) Separating independent units.            

               (D) Break up of data into separate physical units.

       c.      Multiple data sources are combined in

(A) Data cleaning.                                    (B) Data presentation.

(C) Data transforming.                             (D) Knowledge representation.

       d. Which of the following is true?

(A) Snowflake Schema is a normalized star schema

               (B) Dimension tables are normalized in Snowflake Schema

(C) Both (A) and (B) are true

               (D) Only (A) is true

       e.      Data cleaning operation is required to consolidate data such that it may not have

(A) Missing information for a column.

(B) Orphan records.

(C) Outlier data points.

(D) All of the above.

       f.      MBR (Memory Based Reasoning) is used to

(A) Forecast Future Situation.

(B) Ensure data integrity.

(C) Count granularity level.

(D)  Conclude based on global schema.

       g.      ETL implies

(A) Extraction, Transformation and Loading.

(B) External Transaction Link.

(C) Extracted Transmission Library.

(D) None of the above.

      h.      4GL technology helps in

(A) High level programming.

               (B) Accessing database.

(C) Interacting with machine using machine level language.

               (D) Enhancing intelligence in data warehousing.

       i.       The beginning point for the migration plan is

(A) Corporate Data Model.                     (B) External Data Model.

(C) Internal Data Model.                         (D) Meta Data Model.

       j.      Which one of the following is not an OLAP operation?

(A) Drill-up                                             (B) Drill-down

(C) Drill-across (D) Drill-through

Answer any FIVE Questions out of EIGHT Questions.

Each question carries 16 marks.

Q.2     a.   Is a data warehouse a Decision Support System (DSS)? Justify your answer. (6)

             b.   What is Apriori algorithm used for? Write down the algorithm. (10)

Q.3     a.   What are the differences between primitive and derived data? (8)

             b.   Elaborate the major operating components, which are regularly monitored in data warehouse environment.                                                             (8)

Q.4     a.   What role data marts play in virtual data warehouse? Substantiate your answer by clarifying the terms data marts and virtual data warehouse. (8)

             b.   What are problems in implementing data warehouse?                                          (8)

Q.5     a.   Briefly explain MetaData? List the items the MetaData store tracks.                    (8)

             b.   What are the different levels of data modeling? Briefly explain midlevel data modeling.                     (8)

Q.6     a.   What is the relevance of Data Warehouse in an EIS?                                          (8) (8)

             b.   Briefly explain drill-up and drill–down analysis. (8)

Q.7     a.   What is a star schema?  Explain in detail.  How are dimension tables and fact table linked to each other?  Explain the usability of both the tables in the schema.                                                          (8)

             b.   Discuss the issues that should be considered during data integration? (4)

             c.   Why is a feedback loop important for the success of data warehouse implementation?                    (4)

Q.8     a.   Explain implementation of Migration Plan in a Corporate Data Model with the help of a block diagram.       (10)

             b.   Differentiate between OLTP and OLAP.                                                         (6)

Q.9 Write short note on the followings:

                   (i)   Data cleaning.                                                                                              (5)

                   (ii)  Data Cube Technology.                                                                               (6)

                   (iii) Association Rules.                                                                                        (5)