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CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE EVENT_CODE APR2016 ASSESSMENT_CODE MCA5043_APR2016 QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 11567 QUESTION_TEXT List the objectives of data mining in telecommunication. SCHEME OF EVALUATION 1.Helps to understand the business involved, identify telecommunication patterns, catch fraudulent activities, make better use of resources and improve the quality of service. 2.Algorithms include CART, c4.5, neural networks and Bayesian classifiers among others. 3.The ability to handle noise in this case is obviously critical to the successful application of data mining algorithms. 4.The company’s face the problem of churning. 5.Data mining is one solution to do appropriate credit scoring and to combat churns in the telecom industry. 6.Used to churn analysis to perform 2 key tasks: Predict and Understand. 7.Decision support in telecommunication forms the rules that can be used as decision support rules. 8.In central system RTKP procedure based on conjunctive and disjunctive matrices and operators. 9.KDD has delivered a variety technique to discover patterns from vast amount of data which helps in mining for complex data. QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 11572 QUESTION_TEXT Explain various characteristics of data warehouse? 1.Subject oriented 2.Integrated SCHEME OF EVALUATION 3.Non Volatile 4.Time variant (2.5 marks each)(10 marks) QUESTION_T DESCRIPTIVE_QUESTION YPE QUESTION_ID 72810 QUESTION_T Differentiate between OLTP and Data Warehouse. EXT Application databases are OLTP systems where every transaction has to be recorded as and when it occurs. A Data Warehouse on the other end is a database that is designed for facilitating querying and analysis. (1 mark) OLTP VS Data Warehouse: SCHEME OF EVALUATION (9 marks) QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 72812 QUESTION_TEXT What is Data Loading in Data Warehouse? Explain different types of Data Loading. SCHEME OF EVALUATION Data Loading implies physical movement of the data from the computer(s) storing the source database(s) to that which will store the data warehouse database, assuming it is different. (1 mark) Data Loading Types: Initial Load: (3 marks) Populating all the Data Warehouse tables for the very first time. Creation of indexes on initial loads or full refreshes requires special consideration. Index creation on mass loads can be too timeconsuming. So drop the indexes prior to the loads to make the loads go quicker. You may rebuild or regenerate the indexes when the loads are complete. Incremental Load: (3 marks) Applying ongoing changes as necessary in a periodic manner. These are the application of ongoing changes from the source systems. Changes to the source systems are always tied to specific times, irrespective of whether or not they are based on explicit time stamps in the source systems. Full Refresh: (3 marks) Completely erasing the contents of one or more tables and reloading with fresh data. This type of application of data involves periodically rewriting the entire Data Warehouse. Sometimes partial refreshes also requires rewriting only specific tables. Partial refreshes are rare because every dimension table is intricately tied to the fact table. As far as the data application modes are concerned, full refresh is similar to the initial load. However in the case of full refreshes, data exists in the target tables before incoming data is applied. QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 126112 QUESTION_TEXT Explain briefly a. Hierarchical clustering b. Divisive clustering SCHEME OF EVALUATION a. b. QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 126114 QUESTION_TEXT Hierarchical clustering (5 marks) Divisive clustering (5 marks) Discuss the following data warehouse schema a. Star schema b. Snowflake schema a. Star schema (5 marks) b. Snowflake schema (5 marks) SCHEME OF EVALUATION