C1000-065 Exam Dumps : IBM Cognos Analytics Developer V11.1.x

Understanding Joins: Outer joins and cross joins often result in large intermediate result sets. This can slow down query performance due to the increased data processing required.

Outer Joins: These include rows that do not have matching keys in the joined tables, which means more data to process and potentially more I/O operations.

Cross Joins: These produce Cartesian products of the involved tables. If the tables are large, the resulting dataset can be enormous, leading to significant performance degradation.

Cognos Documentation: The IBM Cognos Analytics V11.1.x documentation advises optimizing join conditions and limiting the use of complex joins such as outer and cross joins to enhance performance.

Query Performance: Enhancing query performance involves various optimization techniques.

Avoid Functions in Filters: Using functions in filters can lead to slower query performance because functions often require additional computation and can prevent the database from using indexes efficiently.

Best Practices: It is recommended to simplify filters and avoid complex functions to ensure queries run faster.

Reference: IBM Cognos Analytics V11.1.x documentation suggests avoiding the use of functions in filters as a best practice for improving query performance.