CS614 Final Term Solved Subjective by Junaid

Q1. Different metrics used for comparison data mining techniques. Name the metrics?

•  Accuracy
•  Speed
•  Robustness
•  Scalability
•  Interpretability

2. Three dimensions common in context of Web data warehouse.

•  Some are standard dimensions.
•  Other are non-standard and different.
•  Some of the dimensions for a Web DWH

Q3. Time complexity of K means O(tkn), t=? k=? n=?

ANSER: Formula: Euclidean Distance:

New Centralized Formula:

Q4. Identity header row and how columns delimited?

Q6. Quality Management Grid keys?

•  Uncertainly
•  Awaking
•  Enlightenment
•  Wisdom
•  Certainly

7. Parallel Hardware Architectures

•  Symmetric Multi-process (SMP)
•  Distribution Memory
•  Non-Unifor Memory Access (NUMA)

8. Parallel Software Architectures

•  Shared Nothing
•  Shared Memory
•  Shard Disk

9. OLAP implementation technique

•  MOLAP
•  ROLAP
•  HOLAP
•  DOLAP

Q10. What is wisdom application?

Answer: The app allows users to login to find conversations and join them live or listen on demand. The idea is that the conversation revolves around advice.

11. Kimball lifecycle

Answer: It is successfully used by thousands of data warehouse and business intelligence (DW/BI) project teams across virtually every industry, application domain, business function, and technology platform.

•  Focus on adding business value across the enterprise
•  Dimensionally structure the data that’s delivered to the business

12. Shared nothing RDBMS architecture

ANSWERR: HANDOUTS PAGE 211

13. ERD diagram relationship.

Answer: In an ER diagram, relationship types are represented by diamonds and connect entities with lines. A set of relations of the same type is called a relation se.

14. import export Work.

Answer: DTS can import data from text files or OLE DB data. Alternatively, you can export data from SQL Server to an OLE DB data destination. DTS also enables fast loading of data from text files into SQL Server tables.

15. Data mining.

Answer: Data Means (Raw fact) And Mining means (Extraction) DEFINE: It is a process extraction of useful information from large amount of Data. Data Mining is KDD process KDD stand for (Knowledge Data Discovering) After Discovering the Data it first cleared the data then integrate the data the select the data and after that Transformation data. There are Many Techniques in DM

•  Association
•  Classification
•  Clustering
•  Prediction
•  Regression

16. Data implementation strategies

Answer: There are two Strategies of Data implementation:

•  Top-Down Approach
•  Bottom-Up Approach

Top-Down Approach: Top-Down Approach is generally useful for projects where the Technology is mature and well understand. Bottom-Up Approach: This approach is used when the Business goal is achieved by Data Warehouse.

17. Dense and spare

Dense Index: Every key in the data file is represented in the index file FOR EXAMPLE:

Sparse Index: It has some of the Record

18. Bit Map.

H H H P1 P1 P1 H H H P2 P2 P2