UNIT -1 UNIT -II. Q. 4 Why is entity-relationship modeling technique not suitable for the data warehouse? How is dimensional modeling different?

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1 (Please write your Roll No. immediately) End-Term Examination Fourth Semester [MCA] MAY-JUNE 2006 Roll No. Paper Code: MCA-202 (ID ) Subject: Data Warehousing & Data Mining Time: 3 Hours Maximum Marks: 60 Note: Question no. 1 is compulsory and carries 20 marks. Apart from question 1, the question paper consist of four units each containing two questions carrying 10 marks each. You must attempt one question from each unit. Q. 1 (a) Define information crisis. (b) How data is different from information? (c) Provide functional definition of a data warehouse. (d) Which type of activities are covered under data cleaning. (e) Explain briefly the significance of JAD techniques. (f) How ER modeling is different from dimensional modeling? (g) A dimension table is wide; the fact table is deep. Do you agree? Why / why not? (h)are the junk dimensions necessary in a data warehouse? (i) What do you understand by slice-and dice. (j) Is the data warehouses a pre-requisite for data mining. Why/ why not. UNIT -1 Q. 2 Data warehousing is the only viable means to resolve the information crisis and to provide strategic information. List five reasons to support this assertion and explain them. Q. 3 How are the top-down and bottom-up approaches for building a data warehouse different? Discuss the advantages and disadvantages of each approach. UNIT -II Q. 4 Why is entity-relationship modeling technique not suitable for the data warehouse? How is dimensional modeling different? Q. 5 How does a snowflake scheme differs from a STAR schema. Explain with an example. Name any two disadvantages of snowflake schema. UNIT -III Q. 6 What are the essential differences between MOLAP and ROLAP models. Also list a few similarities.

2 Q. 7 State any five of Dr. Cod s guidelines for an OLAP system, giving brief description of each. UNIT -1V Q. 8 Discuss various application of data mining. Q. 9 How OLAP is different from data mining. Explain using example

3 (Please Write your Exam Roll No. immediately) Roll No... END-TERM EXAMINATION FIFTH SEMESTER [MCA] - DECEMBER 2004 Paper Code: MCA-323 Subject: Data Warehousing and Data Mining Time: 3 Hours Maximum Marks: 60 Note: Attempt five questions in all including Q. 1 which is compulsory. Q. 1. Compulsory Question; Attempt any six parts 12 (a) What are the conceptual features of Data Warehousing which makes it superior to conventional DBMS? (b) Differentiate data mart and data warehouse (c) Multi dimensional databases versus two dimensional conventional databases. (d) Legacy and operational databases (e) Compare data mining concepts with conventional mining engineer. (f) Describe ROLAP (g) Data Integration (h) Cluster analysis and its application (i) Discuss contents of meta data repository. Q. 2. (a) Differentiate operational database system and data warehouses. Some times data warehousing also is termed from tables and spread sheets to data cubes. Comment 4 (b) Discuss Data Warehouse architecture, specifically describe 3-tier data warehouse architecture. 8 Q. 3. (a) Describe various approaches of data mining. 5 (b) CRM (Customer Relation Management) is considered to be and ideal application of data mining. Illustrate this if you were given data on spending habit of famous credit card holders. 7 Q. 4. What are the difference between three main types of data warehouse usage, information processing, analytical processing, and data mining? Also discuss the motivation behind OLAP mining (OLAM). 12 Q. 5. (a) Describe various steps to build a data warehouse in an organization, say in banking sector. 6 (b) What is level of granularity, how will you decide on the level of granualering in your data for data warehouse. 4

4 Q. 6. (a) KDD is really a good example of convergence of technologies where disciplines like statistics, graphics, mathematical and other analytical tools support KDD. Discuss with example. 6 (b) Data warehousing and data mining concepts have provided new approval for DSS. Discuss. 6 Q. 7. (a) Differentiate stationary, distributed and virtual data warehouses. 6 (b) Describe use of Fuzzy logic and its tools in data mining. 6 Q. 8. Write short notes on any two topics 12 (a) Data mining using neural versus genetic algorithm (b) Data web its applications (c) Data models on Data warehousing (d) Data warehousing system for EIS

5 (Please Write your Exam Roll No. immediately) Roll No... END-TERM EXAMINATION FIFTH SEMESTER [MCA] - DECEMBER 2002 Paper Code: MCA-323 Subject: Data Warehousing and Data Mining Time: 3 Hours Maximum Marks: 60 Note: Attempt any five questions. Q. 1. (a) What can data mining do? What are the various approaches of Data Mining? 6 (b) What are the goals and components of a data warehouses? Describe its scope and practical implications. 6 Q. 2. (a) Compare LAN based data warehouse with stage data warehouse. 6 (b) How do differentiate between stationary, distributed and virtual data warehouses. Give appropriate example. 6 Q. 3. Differentiate between the following :- (e) 2-tier, 3-tier and 4-tier data warehouses. 8 (f) Meta data and operational data. 4 Q. 4. Discuss knowledge discovery through statistical techniques in detail. Compare this with knowledge discovery through neural networks. 12 Q. 5. What is a Datamart? What are the advantages of using OLAP databases for decision support? Give appropriate example. 12 Q. 6. Explain the difference between OLTP and OLAP? What are the various DSS topologies and multidimensional databases? Explain with the help of appropriate examples. 12 Q. 7. (a) When do we prefer to use Neural Networks in data mining? What are the limitations and consequences of choosing neural networks in DSS? 6 (b) What is Data partitioning? How do we use data mining for Customer relation Management (CRM)? 6 Q. 8. Write short notes on any two topics 6+6 (g) Fuzzy techniques for Data Mining (h) Data Mining using Genetic Algorithms (i) Data warehouse architecture

6 Please write your Exam Roll No.) Exam Roll No.... END TERM EXAMINATION FOURTH SEMESTER [MCA]-MAY-2008 Paper Code:MCA-202 Paper Id:44202 Subject:Data Warehousing and Data Mining (Batch: ) Time : 3 Hours Maximum Marks : 60 NOTE: Attempt any five questions:- Q1. Attempt any two of the following: (a) What is a data warehouse? Explain different characteristics of a data warehouse? (6) (b) Data warehouse is the only viable means to resolve the information crisis and to provide strategic information. List four reasons to support this and explain them. (6) (c) Describe five differences between operational database and data warehouse. (6) Q2. (a) Explain different types of data used in the data warehouse. (6) (b) What do you mean by strategic information? What are different characteristics of strategic information? For a commercial bank, name five types of strategic information. (6) Q3. (a) Explain past decision support-system. Why the entire past were attempts by IT to provide strategic information failed? (6) (b) Explain information package diagram with suitable example? (6) Q4. (a) You are the vice president of marketing for a nation wide appliance manufacturer with three production plants. Describe the three different ways you will tend to analyze your sales. What are the business dimensions for your analysis? Make a star schema. (8) (b) A dimension table is wide. A fact table is deep. Explain. (4) Q5. (a) Describe slowly changing dimensions. What are the three types? Explain each type with suitable example. (6) (b) What is factless fact table? Design a star schema with a factless fact table to track patients in a hospital by diagnostic procedure and time. (6) Q6. (a) Explain different OLAP operations with suitable example? (6) (b) What are the essential differences between the MOLAP and ROLAP models? Also list few similarities? (6) Q7. Attempt any two of the following:- (a) Discuss the role of data mining in data warehousing. (6) (b) Explain different data mining activities in details? (6) (c) How is data mining different from OLAP? Explain briefly. (6) Q8. Write short notes on any three:- (4x3=12) (a) Decision Tree (b) Snowflake Schema (c) Dimensional Modeling (d) Aggregate fact tables

7 END TERM EXAMINATION FOURTH SEMESTER [MCA] MAY JUNE 2009 Paper Code: MCA-202 Subject: Data Warehousing &Data Mining Paper Id (Batch: ) Time : 3 Hours Maximum Marks : 60 Note: Part -I is compulsory. Attempt any one question from each parts(partii-v) Part I Attempt any ten questions. Each question carries equal marks 2* 10=20 1. What do you mean by strategic information? 2. Explain the term Data warehouse 3. Why is metadata especially important in a data warehouse? 4. What do you mean by web-enabled data warehouse? 5. Explain dimensional hierarchies with two examples. 6. Explain data granularity in a data warehouse 7. Write two advantages of Star Schema. 8. What is meant by slice and dice? Give examples. 9. Differentiate between ROLAP and MOLAP. 10. In what way Data warehouse is a pre-requisite for Data mining? 11. How is the Data mining is primary step in the process of knowledge discovery? 12. Explain cleaning and integration operations of Data mining. PART-II Q1. a) Draw and Explain Basic Building Blocks of Data warehouse. b) What are the Seven deadly sins of building a Data warehouse? Q2 a) How Data warehousing categorizes the business problems? b) What are the three major types of metadata in a data warehouse? Explain the purpose of each type. 1 * 10 =10 PART-III Q1. How can we represent multidimensional data model in Data warehousing? Explain i) Data cube ii) Fact Table ii) Lattice of Cuboids Q2. What is Schema? Explain and Compare Star and Snow Flake Schema for Sales department of LG Electronics Ltd with the dimensions: Time, Branch, Item location, City and Supplier. 1 * 10 =10 PART IV Q.1 a) What are the basic OLAP operations of Multidimensional Data Model? Explain each of them with example. b) Draw and Explain architecture of MOLAP. Q2. a) What are Multidimensional Databases (MDDBS)? How do these store data? b) Compare and summarize the major distinguished feature between OLTP and OLAP.

8 1 * 10 =10 PART-V Q1. a) How neural networks are used in data mining? Explain b) What is Data mining? Briefly explain Knowledge Discovery Process of Data mining with the examples. Q.2. a) Define Data mining and motivation for Data mining? b) What are the basic data mining techniques? Explain any two with example. 1 * 10 =10

9 (please write your Exam Roll No.) Exam Roll No.... END TERM EXAMINATION FOURTH SEMESTER [MCA] MAY-2010 Paper Code: MCA 202 Subject: Data Warehousing and Data Mining Paper ID: Time : 3 Hours Maximum Marks : 60 Note: Question 1 is compulsory. Attempt one question from each unit. Q1. (a) What is an information crisis? (2 x 10=20) (b) Explain different types of data used in data warehouse. (c) What is a data mart? Cive example. (d) What is a factless fact table? Explain with example. (e) How does a snowflake schema differ from STAR Schema? (f) What are junk dimensions? Are they necessary in a data warehouse? (g) Discuss reasons why feeding data into the OLAP system directly from the source operational system is not recommended. (h) What are various factors for consideration in OLAP administration? (i) What are the criteria for evaluating data mining tools? (j) How is data mining the primary step in the process of knowledge discovery? Unit-I Q2. (a) You are senior analyst in the IT department of a company manufacturing automobile parts. The marketing VP is complaining about the poor response by IT in providing strategic information. Draft a proposal to him explaining the reason for the problem and why a data warehouse would be the only viable solution. (8) (b) What are advantages and disadvantages of using top- down approach for building a data warehouse? (2) Q3. (a) What is information package diagram (IPD)? How does it help in dimensional analysis? Make an IPD of sale anaysis System. (7) (b) What do you mean by information system? How is different from operation System? (3) Unit-II Q4. (a) What is star schema? What are its component tabes? Expain by considering suitable example of a supermarket chain. (7) (b) Why is the entity- relationship modeling technique not suitable for a data warehouse? How is dimensional modeling different? (3) Q5. (a) A sale organization builds its data warehouse. It is hnown that not all products are sold at each outlet every day. Show how the use of aggeregatin can speedup analysis. (5) (b) Differentiate between slowly changing and rapidly changing dimensions. (5)

10 Unit-III Q6. (a) You are asked to form to evaluate the MOLAP and ROLAP models and make your recommendations for large manufacturer of heavy chemicals. Describe the criteria your team will use to make the evaluation and selection. (7) (b) What are hypercubes? How do they apply in an OLAP system? (3) Q7. (a) Pick any five of codd s guidelines for OLAP, give reason why the selected guidelines are important for OLAP. (5) (b) Exlain different OLAP operations with suitable example. (5) Unit-IV Q8. (a) What is data mining? Compare various data mining techniques. (5) (b) Explain knowledge variows discovery process in details. (5) Q9. (a) Do neural network and genetic algorithm have anything common? Point out few differences? (5) (b) How is data mining different from OLAP? Explain briefly. (5)

11 (Please write your Exam. Roll No.) Exam. Roll No.. END TERM EXAMINATION FOURTH SEMESTER [MCA], MAY-2011 Paper Code : MCA 204 Subject : Data Warehousing and Data Mining Paper ID : Time: 3 Hours Maximum Marks : 60 Note : Part 1 is compulsory. Attempt one question from each other parts. PART I (2 10=20) Q. 1. Attempt any TEN questions. Each questions carry equal marks. (a) Define Data mining and Data warehousing. (b) Explain correlation analysis for handling redundancy. (c) When is data mart appropriate? (d) What do you mean by web enabled data warehouse? (e) Explain cross table reporting. (f) Explain data granularity in a data warehouse. (g) Distinguish between classification and clustering. (h) List out any two various commercial data mining tools. (i) Write the advantages of ROLAP and MOLAP. (j) Mention the various types of data available in data mining. (k) How Data mining is the primary step in the process of knowledge discovery? (l)explain Data cleaning. PART II Q. 2 (a) Describe five differences between operational system and informational systems. (b) Explain data granularity and how it is applicable to the data warehouse. OR Q. 3 (a) What are the various data sources for the data warehouse? (b) What type of processing take place in a data warehouse? Explain. (2x5=10) 1

12 PART III Q. 4 (a) What is the STAR schema? What are the component tables? (b) For a manufacturing company, design a family of three STARS to support the value chain. (2x5=10) OR Q. 5 (a) Why is the entity-relationship modelling technique not suitable for the data warehouse? How is the dimensional modelling different? (b) Explain (i) Families of STARS (ii) Snowflake Schema. PART IV Q. 6 (a) What is Multidimensional Database? How do these store data? (b) Draw and explain Architechture of MOLAP. (2x5=10) OR Q. 7 (a) What is meant by Slice-and-dice? Explain with an example. (b) Compare and summarise the major distinguished features between OLTP and OLAP. PART V Q. 8 (a) How is data mining different from OLAP?? Explain. (b) What is clustering? How does it differ from classification? Explain with examples. OR Q. 9 (a) Explain cluster detection technique. (b) What is spatial data mining? Explain with example. (2x5=10) 2

13 (Please Write your Exam Roll No. immediately) Examination Roll.No... END TERM EXAMINATION FOURTH SEMESTER [MCA]MAY JUNE 2012 Paper Code: MCA 204 Time:3 Hours Subject: Data Warehousing & Data Mining Maximum Marks:60 Note: Attempt five question including Q.no.1 which is compulsory. Select one Question from each unit. Question 1 :- (a)what is strategic information? (b What is data mart? When is it appropriate? (c)data warehousing and data mining creates intelligence in business. Justify. (d)what are the advantages of snowflake schema over star schema? (e)what are hypercubes?. (f)discuss reasons why feeding data into the OLAP system directly from the source operational system is not recommended? (g)is the data warehouse a pre-requisite for data mining? Why/Why not? (h)define support and confidence for an association rule. (i)explain correlation analysis for handling redundancy. (j)compute the Euclidean and Manhattan distance between the two objects represented by following tuples (1,6,2,5,3) and (3,5,2,6,6). (2*10=20) UNIT-I Q2(a)Describe five differences between operational system and informational systems. (5) (b)explain data granularity and how it is applicable to the data warehouse. (5) Q3(a)What a information package diagram(ipd)? How it helps in dimensional analysis? Make an IPD of Hotel occupancy system.. (7)

14 (b)what are the advantages and disadvantages of using bottom-up approach for building a data warehouse? (3) UNIT II Q4(a)What is dimensional modeling? How it is different from E-R modeling? (3) (b)what is STAR schema? Explain by taking example. A dimension table is wide and fact table is deep. Justify. (7) Q5(a)Describe slowly changing dimensions. What are the three types of change? Explain each type briefly. (5) (b)draw and explain architecture of MOLAP. What are the advantages of MOLAP over ROLAP? (5) UNIT-III Q6(a)How is data mining different from OLAP? What are the advantages of data mining? Explain briefly.. (5) (b)explain knowledge discovery Process(KDD) in details.. (5) Q7(a)What is data cleaning? Explain various smoothing techniques of noisy data. (5) (b)list and describe the five primitives for specifying a data mining task. (5) UNIT-IV Q8(a)You are the marketing manager of LG electronics and would like to characterize the buying habits of customers who PURCHASE items in North India [city<state<region<country] and priced not less than Rs 5000 w.r.t. CUSTOMER s age, type of ITEM purchased, the place in which ITEM was made. For each characteristic discovered, you would like to know the % of customers with 5% noise threshold having that characteristic. The result should be in the tabular form. Write DMQL for it. (5) (b) What is classification? Describe decision tree technique of classification with example. (5) Q9(a) The following six objects each with two attributes are to be clustered A1(4,6) A2(2,6) A3(9,3) A4(6,9) A5(7,5) A6(5,7) :-

15 (i)show the distance matrix for six objects using the Manhattan distance. (ii)using the divisive methods determine the two objects that should form the basis for splitting the above dataset. (iii)now split the dataset using the two objects identified in part(ii) using the k- means method. (5) (b)briefly explain different data mining applications. (5)

UNIT -1 UNIT -II. Q. 4 Why is entity-relationship modeling technique not suitable for the data warehouse? How is dimensional modeling different?

UNIT -1 UNIT -II. Q. 4 Why is entity-relationship modeling technique not suitable for the data warehouse? How is dimensional modeling different? (Please write your Roll No. immediately) End-Term Examination Fourth Semester [MCA] MAY-JUNE 2006 Roll No. Paper Code: MCA-202 (ID -44202) Subject: Data Warehousing & Data Mining Note: Question no. 1 is