With the latest Market trend MDM-BO integration is emerging as it results in cleanse data and lot of other benefits. On the other hand we don't have any function available under MDM Expressions in MDM Data Manager for removing special characters. So other than MDM-BO do we have any other alternative ? Everyone will have different views on it. But still I feel that MDM Import Manager is very impressive tool for removing special characters effectively and doing other conversions before entering data into MDM.
So I want to tell here some of the capabilities and functionalities of MDM Import Manager for cleansing data before entering data into MDM.
See, when you right click on source field, you can have there property->Set Value Conversion Filter->Multiple
1. Apply Operator
2. Normalize
3. Change Case
4. Replace
5. Accept Truncated Value
Points to be noted:
1.One of the Most Important aspects for playing about these Properties depends on the Type of field defined in MDM.
2.You can set these Properties only after mapping your source field with target field.
Now if you map your source field with MDM field of TYPE INTEGER
After right click on source field->Set Value Conversion Filter->Multiple
Here you can play with only Apply Operator
You can set operator for your source values as +, -, x, /, equals, Null Equals, Round, Ceiling, Truncate.
These functions are very useful in case if you want your source field values to be multiplied by some certain digit before coming into MDM, there we can use multiply operator "x". Similarly other operators one can be used as per requirement.
Now if you map your source field with MDM field of TYPE TEXT
After right click on source field->Set Value Conversion Filter->Multiple
Here you can play with Apply Operator (Append and Prepend only) as well as other filters like Normalize, Change Case, Replace, Accept Truncated Value.
Here I will discuss only Normalize, Change Case and Replace functionalities.
Sometimes we have requirement for removing special characters like @, &, #, $ etc. So question is when to go for Normalize and when to go for Replace Conversion filters.
If there is requirement to remove everything including spaces too then one should go for Normalize functionalities.
E.g. if field has value Lexan$@ ID& 300
So outcome after Normalizing would be LEXANID300
You can also make use of CHANGE CASE (UPPER CASE, lower case, Title case etc) along with Normalize as per your requirement. If you also set Change Case = Sentence Case, along with Normalize you will get output as Lexanid300
But if you want to keep spaces between tokens and only want to get rid of special characters, you should go ahead with REPLACE. Other benefit, you can remove the specific special characters if there is requirement. In other words Custom Special characters removal.
E.g. if field has value Lexan$@ ID& 300
Requirement is just to remove special characters @ and &, so here you are maintaining $ as well as SPACES between tokens. Set Replace as shown in below screen-shot.
You will get desired result as shown below where symbol $ and SPACES are maintained between different tokens.
I am not sidelining the benefits of MDM-BO integration but just wanted to aware everyone that MDM Import Manager is also proficient up to certain extent in dealing with cleansing of data. I hope this blog would be useful and informative for everyone especially MDM Beginners.
So I want to tell here some of the capabilities and functionalities of MDM Import Manager for cleansing data before entering data into MDM.
See, when you right click on source field, you can have there property->Set Value Conversion Filter->Multiple
1. Apply Operator
2. Normalize
3. Change Case
4. Replace
5. Accept Truncated Value
Points to be noted:
1.One of the Most Important aspects for playing about these Properties depends on the Type of field defined in MDM.
2.You can set these Properties only after mapping your source field with target field.
Now if you map your source field with MDM field of TYPE INTEGER
After right click on source field->Set Value Conversion Filter->Multiple
Here you can play with only Apply Operator
You can set operator for your source values as +, -, x, /, equals, Null Equals, Round, Ceiling, Truncate.
These functions are very useful in case if you want your source field values to be multiplied by some certain digit before coming into MDM, there we can use multiply operator "x". Similarly other operators one can be used as per requirement.
Now if you map your source field with MDM field of TYPE TEXT
After right click on source field->Set Value Conversion Filter->Multiple
Here you can play with Apply Operator (Append and Prepend only) as well as other filters like Normalize, Change Case, Replace, Accept Truncated Value.
Here I will discuss only Normalize, Change Case and Replace functionalities.
Sometimes we have requirement for removing special characters like @, &, #, $ etc. So question is when to go for Normalize and when to go for Replace Conversion filters.
If there is requirement to remove everything including spaces too then one should go for Normalize functionalities.
E.g. if field has value Lexan$@ ID& 300
So outcome after Normalizing would be LEXANID300
You can also make use of CHANGE CASE (UPPER CASE, lower case, Title case etc) along with Normalize as per your requirement. If you also set Change Case = Sentence Case, along with Normalize you will get output as Lexanid300
But if you want to keep spaces between tokens and only want to get rid of special characters, you should go ahead with REPLACE. Other benefit, you can remove the specific special characters if there is requirement. In other words Custom Special characters removal.
E.g. if field has value Lexan$@ ID& 300
Requirement is just to remove special characters @ and &, so here you are maintaining $ as well as SPACES between tokens. Set Replace as shown in below screen-shot.
You will get desired result as shown below where symbol $ and SPACES are maintained between different tokens.
I am not sidelining the benefits of MDM-BO integration but just wanted to aware everyone that MDM Import Manager is also proficient up to certain extent in dealing with cleansing of data. I hope this blog would be useful and informative for everyone especially MDM Beginners.
