Below are some important SAP BO interview questions which are asked in most MNC company interviews for beginners or professionals.
31. What is Data Cleanse?
The Data Cleanse transform identifies and isolates specific parts of mixed data, and standardizes your data based on information stored in the parsing dictionary, business rules defined in the rule file, and expressions defined in the pattern file.
32. What is the difference between Dictionary and Directory?
Directories provide information on addresses from postal authorities. Dictionary files are used to identify, parse, and standardize data such as names, titles, and firm data.
33. Give some examples of how data can be enhanced through the data cleanse transform, and describe the benefit of those enhancements.
? Enhancement Benefit
? Determine gender distributions and target
? Gender Codes marketing campaigns
? Provide fields for improving matching
? Match Standards results
34. A project requires the parsing of names into given and family, validating address information, and finding duplicates across several systems. Name the transforms needed and the task they will perform.
? Data Cleanse: Parse names into given and family.
? Address Cleanse: Validate address information.
? Match: Find duplicates.
35. Describe when to use the USA Regulatory and Global Address Cleanse transforms.
Use the USA Regulatory transform if USPS certification and/or additional options such as DPV and Geocode are required. Global Address Cleanse should be utilized when processing multi-country data.
36. Give two examples of how the Data Cleanse transform can enhance (append) data.
The Data Cleanse transform can generate name match standards and greetings. It can also assign gender codes and prenames such as Mr. and Mrs.
37. What are name match standards and how are they used?
Name match standards illustrate the multiple ways a name can be represented.They are used in the match process to greatly increase match results.
38. What are the different strategies you can use to avoid duplicate rows of data when re-loading a job.
? Using the auto-correct load option in the target table.
? Including the Table Comparison transform in the data flow.
? Designing the data flow to completely replace the target table during each execution.
? Including a preload SQL statement to execute before the table loads.
39. What is the use of Auto Correct Load?
It does not allow duplicated data entering into the target table.It works like Type 1 Insert else Update the rows based on Non-matching and matching data respectively.
40. What is the use of Array fetch size?
Array fetch size indicates the number of rows retrieved in a single request to a source database. The default value is 1000. Higher numbers reduce requests, lowering network traffic, and possibly improve performance. The maximum value is 5000
31. What is Data Cleanse?
The Data Cleanse transform identifies and isolates specific parts of mixed data, and standardizes your data based on information stored in the parsing dictionary, business rules defined in the rule file, and expressions defined in the pattern file.
32. What is the difference between Dictionary and Directory?
Directories provide information on addresses from postal authorities. Dictionary files are used to identify, parse, and standardize data such as names, titles, and firm data.
33. Give some examples of how data can be enhanced through the data cleanse transform, and describe the benefit of those enhancements.
? Enhancement Benefit
? Determine gender distributions and target
? Gender Codes marketing campaigns
? Provide fields for improving matching
? Match Standards results
34. A project requires the parsing of names into given and family, validating address information, and finding duplicates across several systems. Name the transforms needed and the task they will perform.
? Data Cleanse: Parse names into given and family.
? Address Cleanse: Validate address information.
? Match: Find duplicates.
35. Describe when to use the USA Regulatory and Global Address Cleanse transforms.
Use the USA Regulatory transform if USPS certification and/or additional options such as DPV and Geocode are required. Global Address Cleanse should be utilized when processing multi-country data.
36. Give two examples of how the Data Cleanse transform can enhance (append) data.
The Data Cleanse transform can generate name match standards and greetings. It can also assign gender codes and prenames such as Mr. and Mrs.
37. What are name match standards and how are they used?
Name match standards illustrate the multiple ways a name can be represented.They are used in the match process to greatly increase match results.
38. What are the different strategies you can use to avoid duplicate rows of data when re-loading a job.
? Using the auto-correct load option in the target table.
? Including the Table Comparison transform in the data flow.
? Designing the data flow to completely replace the target table during each execution.
? Including a preload SQL statement to execute before the table loads.
39. What is the use of Auto Correct Load?
It does not allow duplicated data entering into the target table.It works like Type 1 Insert else Update the rows based on Non-matching and matching data respectively.
40. What is the use of Array fetch size?
Array fetch size indicates the number of rows retrieved in a single request to a source database. The default value is 1000. Higher numbers reduce requests, lowering network traffic, and possibly improve performance. The maximum value is 5000
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