Informatica Data Quality Practice Tests

The practice tests are created to measures your knowledge and competency as an Informatica Data Quality (IDQ) developer who will be a member of any kind of Data Quality projects/implementations. These practice tests cover a lot of ground on in-depth aspects of Data Quality processes such as Profiling, Standardization, Matching, Consolidation, Exception Management and various aspects of configuring the appropriate Data Quality transformations and build the transformations for complex real-time requirements. Additionally, all the other important areas like human tasks, debugging, Reference Data Management, Scorecards, Analyst activities, deployment activities, execute Data Quality mappings, integrating the mappings/rules/mapplets into Informatica Power Center.

Is this an online video-based course?

No. This is a practice test with questions and multiple-choice answers.

Will it be an interactive session?

Yes, you will be able to send a note to the trainer/instructor and communicate as well. If you are taking this course, there are options to see the questions asked by you and also by other participants. This will not only help you to get the questions clarified but also you will know the different perspectives of the subject based on the questions asked by other participants.

Will I get any material apart from the questions and answers?

We will support you with your questions, doubts, and help you with any relatedInformatica corporation documentation and other curated Data Quality specific products content to learn and understand the content/topics with more clarity.

Do these tests cover any real-time scenarios / live project scenarios?

Yes, all the content and questions in this course are from real-time project implementations. Everything will be practical and on real-time project implementation.

Will this help me to clear the IDQcertification?

We encourage you to learn all the topics and prepare for success. All the questions and answers provided here have helped multiple other participants to clear the interviews and IDQcertification without any help. We do help you with any clarifications required.

Please note, these questions are not copy and paste from the actual certification test, these questions are prepared based on the test topics covered in the certification test

Please note, launch the practice test using chrome browser. In other browsers, the question and answers may not fit the window and you may have to scroll the page up and down to see the questions and answers.

Sample Questions

Question 1. A customer file has 5 million records and 500 records are duplicates, the customer data has to be analyzed based on CustomerName, DateofBirth and SSN. Filter Exact Match option is enabled in Match transformation, how the mapping performance will be impacted?

A) Enabling Filter Exact Match option helps improve performance by removing duplicate records out of the matching process. However, there is additional logic (internally added) to remove the duplicate records that adds little overhead to internal mapping logic, hence its not recommended to enable Filter Exact Match option for this scenario.

B) It is recommended to use the Filter Exact Match option and allow the 500 duplicate records go through the matching process, as every row of data goes through the matching process irrespective of selecting Filter Exact Match option.

C) Filter Exact Match option can only be used in Dual Source matching, and in this scenario, the option is disabled by default.

D) It is recommended to group the similar records and send the grouped data to the Match Process instead of using Filter Exact Match option, similar records will be created on the same cluster, which will be (similar records) consolidated and removed by Consolidator transformation.

Correct Answer: A.

For this scenario, it's not recommended to enable the Filter Exact Match option.

Filter Exact Match can be configured in clustered output match type only. When Filter Exact Match is enabled it Improves the performance of the Match Transformation by eliminating the identical records from the matching process. The identical records are directly written to the clustered output.

If you have a source dataset with a large number of identical records enabling Filter Exact Match will improve performance by removing identical records out of the matching process.

Based on the source data and the number of exact matches in the dataset, it has to be checked if Match Mapping can be executed with or without enabling the Filter Exact Match option.

If the data set has a lot of exact matches, there is a lot of overhead to process these exact matches, and Match mapping can be very resource-intensive, to Improve the Match performance in this scenario we can enable the Filter Exact Match Option.

Question 2. Using Data Quality for Excel, 80 records should be processed as one batch, select all the correct answers.

A) Set Maximum Occurrences to unbounded to allow the web service to process multiple records in one batch.

B) In the DQ for excel settings, increase the Batch size to 80

C) In the Data Integration Service, under the Application tab, select the web service which is configured in DQ for excel and update the Maximum Concurrent Requests to 80

D) Users cannot configure the batch size, the records will be processed as per the default batch size of 1 record. Updating the Maximum Concurrent Requests to 80 in the web services 80 records can be processed in parallel.

Correct Answer: A,B

DQ for excel helps non-Informatica users to use the data quality rules created in IDQ and validate data in excel. DQ for excel helps users to reuse the data quality rules and perform data validation from their PC and check how the source data will get transformed into the target data objects.

In IDQ, developer has created a mapplet that will standardize data based on the reference data and parse address or customer names. Developers can save the mapplet as web service and give the web service ( after deploying the web service to application). Users can use the DQ for excel and create a new service(Add) using the web service url and validate the data in excel.

Users can create a batch of 100 records and validate the data using DQ for Excel. The web service Maximum Occurrences should be configured to unbounded to allow the web service to process multiple records in one batch.

Question 3. Data has to be extracted from various sources and compared against the master data for each load, the existing process is delaying the load process due to the source data comparison with master data for every load. The customer is insisting to follow the same load approach and asked your recommendation.

Select the best approach

A) Use Identity Match with Persistent RecordID which uses Universal ID which allows users to store matching keys to make the subsequent matching process efficient. It will significantly improve the performance when source data is matched against master data regularly and the speed of the match operation is critical

B)Standardize the data and perform dual-source matching, as data is standardized by removing the noise words, and validating against the reference tables, the match process will be efficient and load time will be considerably less as compared to performing the match without standardization

C) Reading the data from two pipelines and performing a dual-source is not recommended, when time is a constraint. Use Union transformation to combined the data from both the sources and perform single source Field matching and in consolidation transformation use row-based strategy with modal exact option to prioritize the data from the master source.

D) All the other approaches mentioned will not reduce the load window, as the match process is a complex process. Instead of using match transformation use Comparison transformation to compare strings between source data and master data and based on the score generated to create an ETL process to load as per your requirement.

Correct Answer: A

Use Identity Match with Persistent RecordID which uses Universal ID which allows users to store matching keys to make the subsequent matching process efficient. It will significantly improve the performance when source data is matched against master data regularly and the speed of the match operation is critical