24. For initial load data are extracted for all products from different source system, integrate and transform the data and then create load images for loading data into the A. Product information table Products records C. Product dimension table D. Product sources system 25. Vendors have provided solution for the challenges of ETL by providing function as the following EXCEPT A. Dynamics and sophisticated data manipulation algorithms B. Data capture through stages C. Data capture out of replication D. Generating program code 26. To compare actual sales against sales target and against sales in prior period is analysis knowns as A. Analytical processing B. Multidimensional analysis C. Profitable analysis Strategic analysis 27. The following are the general features of OLAP EXCEPTS A. Easy scalability B. Consistent performance C. Complex calculation D . Collaborative decision making 28. Attributes of the product dimension namely product name, subcategory, category, product line and departments in the OLAP systems are attributes that is called A. Hierarchies of the product dimension B. Hierarchies of the product information C. Hierarchies of the aggregation D. Hierarchies of the Roll-up and drill down 29 The following are TRUE about how ROLAP works EXCEPT A. The user issues query The result from the query is stores in a small, local multidimensional database The user answer queries against the local database D. The user perform analysis against this local database30. The data redundancy is significant and could be the reason of the network problem is an issue related to A. MOLAP B. DOLAP C. ROLAP D. HOLAP 31. Data mining plays a significant role in data warehouse environment. The following and the features of datamining EXCEPT A. Data driven automatic knowledge discovery B. Predict the future based on why this is happening C. Summary data D. Large number of dimensions 32. This algorithm is useful for findings pattern from relationship example "why are low fat milk and brown bread are always in the same transaction about 80% of the time?" A. Link Analysis B. Predictive modelling C. Rule induction D. Database segmentation 33 Data mining is use within the science community and application in the commercial arena. Thus, data mining process is important to ensure the usefulness of the technology. Identify the sequence of the data mining process A. Define problem; select data; mine the data; prepare the model; take business action B. Identify problem; select data; prepare data; mine the data; implement the model; do business action C. Define problem, prepare data; select the best data; mine the data; implement the model; do business action D. Identify problem; analyse data; prepare data; mine the data; use the model; do business action 34. Artificial neural networks mimic the by learning from the dataset and applying the learning to generalize pattern for classification and prediction. A. Human activity B. Human behavior C. Human values D. Human brain 35. Decision trees basic process are A Grouping values in the same neighborhood B. Discover links among variables by their values Split at decision points based on entropy D. Weighted inputs of predictors at each node36. are indicators that provide information on the utilization of the hardware and software resources. A Monitoring statistics B. Collection of statistics C. Event-driven methods D. Sampling method 37. The following are showing the use of statistics in the environment EXCEPT A. Memory management Input and output memory C. Buffer cache usage D. Buffer cache usage 38. User training content must consider that users in an organization are A. Equally skillful and knowledgeable B. Are novel and similar Different in knowledge and ability D. Ready to adapt and adopt the technology 39. User training support are significance because Users tend to be frustrated without good support Users are not ready to learn new technology Users are not ready to use new technology Users are not willing to change their ways of working 40. Data warehouse administration able to manage data growth by Collect all historical data and manage old data Always create additional summary tables to use drill down functions C. Dissuade analyst from holding unplanned summaries D. Gather data details and use drill-down functions