Continuation of the https://che.gg /3EYZKY7 List some meaningful data quality problems: g) Are there any integration problems? (shema integration, data value conflicts, redundant attributes) Do you need to apply any data reduction strategies? h) Do you define new variables, not existing in the original database, to solve the classification (regression) problems? (feature creation) i) Are there some features carrying similar information? Are threre irrelevant features? j) Do you apply any sampling methods? k) What data transformations and/or discritizations are needed? 1) Evaluate the possible solution of one of the data mining problems from the business point of view. i) Suppose one of these three problems is solved successfully. Describe the deployment of the solution in the real environment. What are some possible impacts of the data mining solution? Can you imagine any unanticipated situations after implementation of the solution