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problem 1) With appropriate diagram describe the steps in query processing.

b) Describe how the Pipelines are executed.

c) Describe basic scan algorithms to implement selection operation in query processing.

problem 2)

a) What are the measures of query cost?

b) Describe and compare nested loop join and block nested loop join algorithm.

c) Describe the search algorithm that make use of index.

problem 3)a) Describe parallel database architectures.

b) State the advantages and disadvantages of distributed system.

c) prepare brief note on : Data servers.

problem 4)a) Describe centralized and client server database architectures.

b) Describe transaction server system in detail.

c) Compare and contrast speedup and scaleup.

problem 5)a) Describe structured types and inheritance with ex in SQL.

b) Describe the different approaches used for making an object persistent.

problem 6)a) Describe object identity and reference types with ex.

b) What is persistent programming language and how it is different from embedded language?

problem 7)a) What is the major difference between the snowflake and star schema models?

b) Describe any two operations on data cubes.

c) What do you mean by Data cleaning? Name the different methods for handling the missing values. Describe them in brief.

problem 8)a) Define the following terms with respect to Data Cube:

i) Dimension table

ii) Fact table

iii) Base Cuboid

b) Describe any two data smoothing techniques.

c) prepare brief notes on:

i) Fact Constellation

ii) Need for preprocessing data.

problem 9)a) What is the role of data mining in knowledge discovery process?

b) Describe the following terms with respect to Apriori algorithm.

i) Apriori property

ii) Join action

iii) Prune action.

c) prepare short notes on:

i) Bayesian classifiers

ii) Machine Learning.

problem 10)a) What do you mean by classification? With a appropriate ex describe the concept of Decision Tree.

b) Distinguish between Data Mining and OLAP.

c) prepare brief notes on:

i) K-means algorithm

ii) Outlier analysis

DBMS, Programming

  • Category:- DBMS
  • Reference No.:- M95640

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