You can increase performance by eliminating unnecessary data type conversions.
For example, if a mapping moves data from an Integer column to a Decimal column, then back to an Integer column, the unnecessary data type conversion slows performance. Where possible, eliminate unnecessary data type conversions from mappings.
Use the following data type conversions to improve performance:
•Use integer values in place of other data types when performing comparisons using Lookup and Filter transformations. For example, many databases store U.S. ZIP code information as a Char or Varchar data type. If you convert the zip code data to an Integer data type, the lookup database stores the zip code 94303-1234 as 943031234. This helps increase the speed of the lookup comparisons based on zip code.
•Convert the source dates to strings through field-to-field conversions to increase performance. You can either leave the fields in targets as strings or change the fields to Date/Time fields.