Integration Services NULL Management Tips

One of the biggest challenges in a ETL project is faced during data cleansing. NULLs are one of the most unexpected and problematic issues that can make a SSIS package fail. Defensive programming against NULLs is very important, especially when you are dealing with data migration projects where data from OLTP or other source systems cannot always be predicted. This is a multi-part series of NULL Defense, and in this first part we will look at NULL Defense against dates (datetime data type).

In the previous two parts of the NULL Defense series, we saw how to add NULL Defense at the database level for dates and how to add NULL Defense within our package for scripting. We discussed earlier that NULLs can cause undesirable results in data and can cause transformations to fail. Functions and operators are no exception. NULLs will easily by-pass operators and/or functions without any exception until we investigate the results and finally figure out that NULL values were the cause. In this tip, we will address the issue of how to add NULL Defense to defend our transformations from breaking and shield our operators from generating undesirable results due to NULL values.

As we discussed in the first part of this NULL Defense series, NULL values in data is one of the most common reasons that can make your SSIS package fail. The reason for the same is that many controls are vulnerable to interpret NULL undesirably, which can effectively cause the transformation to either fail or return unexpected results. In this part of NULL Defense series, we will discuss how to create NULL Defense in Script Transformation.

As we discussed in the first part of this NULL Defense series, NULL values in data is one of the most common reasons that can make your SSIS package fail. The reason for the same is that many controls are vulnerable to interpret NULL undesirably, which can effectively cause the transformation to either fail or return unexpected results. In this part of NULL Defense series, we will discuss how to create NULL Defense in Script Transformation.

One of the biggest challenges in a ETL project is faced during data cleansing. NULLs are one of the most unexpected and problematic issues that can make a SSIS package fail. Defensive programming against NULLs is very important, especially when you are dealing with data migration projects where data from OLTP or other source systems cannot always be predicted. This is a multi-part series of NULL Defense, and in this first part we will look at NULL Defense against dates (datetime data type).

In the previous two parts of the NULL Defense series, we saw how to add NULL Defense at the database level for dates and how to add NULL Defense within our package for scripting. We discussed earlier that NULLs can cause undesirable results in data and can cause transformations to fail. Functions and operators are no exception. NULLs will easily by-pass operators and/or functions without any exception until we investigate the results and finally figure out that NULL values were the cause. In this tip, we will address the issue of how to add NULL Defense to defend our transformations from breaking and shield our operators from generating undesirable results due to NULL values.

In the previous two parts of the NULL Defense series, we saw how to add NULL Defense at the database level for dates and how to add NULL Defense within our package for scripting. We discussed earlier that NULLs can cause undesirable results in data and can cause transformations to fail. Functions and operators are no exception. NULLs will easily by-pass operators and/or functions without any exception until we investigate the results and finally figure out that NULL values were the cause. In this tip, we will address the issue of how to add NULL Defense to defend our transformations from breaking and shield our operators from generating undesirable results due to NULL values.

As we discussed in the first part of this NULL Defense series, NULL values in data is one of the most common reasons that can make your SSIS package fail. The reason for the same is that many controls are vulnerable to interpret NULL undesirably, which can effectively cause the transformation to either fail or return unexpected results. In this part of NULL Defense series, we will discuss how to create NULL Defense in Script Transformation.

One of the biggest challenges in a ETL project is faced during data cleansing. NULLs are one of the most unexpected and problematic issues that can make a SSIS package fail. Defensive programming against NULLs is very important, especially when you are dealing with data migration projects where data from OLTP or other source systems cannot always be predicted. This is a multi-part series of NULL Defense, and in this first part we will look at NULL Defense against dates (datetime data type).