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CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE EVENT_CODE APR2016 ASSESSMENT_CODE MC0088_APR2016 QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 5227 QUESTION_TEXT Distinguish the features between OLTP and OLAP SCHEME OF EVALUATION Users and sytem orientatioin: An OLTP system is customer oriented and is used for transaction and query used for transacrion and query processing by clerks,clients and information technology professionals. An OLAP system is market oriented and is usd for data analysis by knowledge workers, including managers, executives and analysts. (2 marks) Data contents: An OLTP system managers current data that typically are too detailed to be easily used for decision making. An OLTP system managers large amounts of historiacl data, provides facilities for summarization and aggregation and stores and managers information at different levels of granularity. These features make the data easier to use in informed decision making. (2 marks) Database design:An OLTP system usually adopts an entity relationship data model and an application oriented database design. An OLAP system typically adopts either a star or snowflake model and subject – oriented database design. (2 marks) View:An OLTP system focuses mainly on the current data within an enterprise or department without referring to historical data or data in different organizations. In contrast OLAP system often spans multiple versions of a database schema, due to the evolutionary process of an organization. OLAP systems also deal with information that originates from different organizations, integrating information from many data stores. Because of their huge volume, OLAP data are stored on multiple storage media. (2 marks) Access patterns: The access patterns of an OLTP system consists manily of short, atomic transactions. Such a system requires concurrency concurrency control and recovery mechanisms. However access to OLAP systems are mostly read only operations although many could be complex queries. (2 marks) (Total 10 marks) QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 72559 Discuss data smoothing technologies. QUESTION_TEXT a. b. SCHEME OF EVALUATION c. d. Binning Clustering Combined computer and human inspection Regression (2.5 marks each with explanation) QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 117785 QUESTION_TEXT Explain the various OLAP data cube operations. The various data cube operations are: ● SCHEME OF EVALUATION ● Roll-up Drill-down ● Slice and dice ● Pivot (Rotate) QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 117789 QUESTION_TEXT What is data cleaning? Explain missing values method for data cleaning. Data cleaning routines attempt to fill in missing values, smooth out noise while identifying outlines, and correct inconsistencies in the data. (2 marks) Missing value Methods are: SCHEME OF EVALUATION 1. Ignore the tuple 2. Fill in the missing value immediately 3. Use a global constant to fill in the missing value (4 marks) 4. Use the attribute value to fill in the missing value 5. Use the attribute mean for all samples belonging to the same class as the given tuple 6. Use the most probable value to fill in the missing value (4 marks) QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 117790 QUESTION_TEXT Define FP-Tree. Explain FP-tree construction Algorithm A frequent pattern tree( or fp-tree) is a tree structure consisting of an item –prefix –tree and a frequent – item-header table. (3 marks) Item – prefix- tree: * * It consists of a root node labelled null * Each on-root node consists of three fields SCHEME OF EVALUATION * Item name * Support count, * Node link Frequent – item – header – table: it consists of two fields: * * * the FP-tree Item name Head of node link which points to the first node in (7 marks) FP-Tree construction algorithm is given in page no: 113 QUESTION_TYPE DESCRIPTIVE_QUESTION QUESTION_ID 117793 QUESTION_TEXT List and explain the various criteria used to compare the classification methods. SCHEME OF EVALUATION Predictive accuracy Speed Robustness Scalability Interpretability 5×2=10 marks