DataStage is a popular ETL (Extract, Transform, Load) tool by IBM InfoSphere Information Server. DataStage is used by organizations working with large data sets and warehouses for data integration from the data source system to the target system. Top DataStage job roles are DataStage Developer, ETL Developer, DataStage Production Manager, etc.  

In this article, we have shared a list of the most frequently asked IBM DataStage interview questions and the answers to the questions. These DataStage interview questions and answers are beneficial for beginners as well as experienced professionals to crack DataStage interviews.  

These questions will cover key concepts like DataStage and Informatica, DataStage routine, lookup stages comparison, join, merge, performance tuning of jobs, repository table, data type conversions, quality state, job control, etc.

Professional Certificate Program in Data Science

The Ultimate Ticket To Top Data Science Job RolesExplore Course
Professional Certificate Program in Data Science

Basic DataStage Interview Questions

1. The most basic dataStage interview question is to define DataStage.

DataStage is an ETL tool that extracts, transforms, and loads tool for Windows servers for data integration from databases into the data warehouse. It is used to design, develop and run different applications to fill data into data warehouses and data marts. DataStage is an essential part of the IBM InfoSphere Data Integration Suite.  

2. What are DataStage characteristics?

DataStage supports the transformation of large volumes of data using a scalable parallel processing approach. 

It supports Big Data Hadoop by accessing Big Data in many ways, like on a distributed file system, JSON support, and JDBC integrator.

DataStage is easy to use, with its improved speed, flexibility, and efficacy for data integration. 

DataStage can be deployed on-premises or in the cloud as need be.

3. How is a DataStage source file populated?

A source file can be filled in many ways, like by creating a SQL query in Oracle, or through a row generator extract tool. 

4. How is merging done in DataStage?

Merging or joining of two or more tables can be done based on the primary key column in the tables. 

5. One of the most frequently asked dataStage interview questions is what is the difference between DataStage 7.0 and 7.5?

DataStage 7.5 comes with many new stages added to version 7.0 for increased stability and smoother performance. The new features include the command stage, procedure stage, generating the report, and more. 

6. What are data and descriptor files?

A data file contains only data, while a descriptor file contains all information or description about data in data files. 

7. One of the most frequntly asked datastage interview questions isDifferentiate between DataStage and Informatica.

Both DataStage and Informatica are powerful ETL tools. While DataStage has the concept of parallelism and partition for node configuration, Informatica does not support parallelism in node configuration. DataStage is simpler to use than Informatica, but Informatica is more scalable. 

Free Course: Introduction to Data Science

Learn the Fundamentals of Data ScienceEnroll Now
Free Course: Introduction to Data Science

8. What is a routine, and what are the types?

A routine is a collection of functions defined by the DataStage manager. There are 3 types of routines, namely parallel routines, mainframe routines, and server routines. 

9. How to write parallel routines. 

Parallel routines can be written in C or C++ compiler. We can also create such routines in DS manager and can be called from the transformer stage. 

10. How are duplicates removed in DataStage?

The sort function can be sued to remove duplicates in DataStage. While running the sort function, the user should specify the option that allows for duplicates and set it to false. 

11. What is the difference between join, merge, and look up stages?

These concepts differ from each other in how they use memory storage, compare input requirements and treat different records. Join and Merge need less memory than Look up. 

12. How to convert server job to parallel job in DataStage?

We can convert a server job into a parallel job with the help of an IPC collector and a link collector.  

13. What is an HBase connector?

It is a tool used to connect databases and tables that are present in the HBase database. It can be used to carry out tasks like:

Read data in parallel mode

Read/write data from and to the HBase database.

Use HBase as a view table

Intermediate DataStage Interview Questions

14. What steps should be taken to improve DataStage jobs?

First, we have to establish baselines. Also, we shouldn’t use only one flow for performance testing. Work should be done incrementally. Evaluate data skews and, thereafter, isolate and solve the problems one by one. Next, distribute the file systems to avoid bottlenecks, if any. Do not include RDBMS at the beginning of the testing phase. Finally, identify and examine the

available tuning knobs. 

15. What is the quality state in DataStage?

The quality stat is used for data cleansing with DataStage tool. It is a client-server software provided as part of IBM information server. 

16. One of the most frequntly asked datastage interview questions isDefine job control.

Job control is a tool used for controlling a job or executing multiple jobs parallelly. The Job Control Language within the IBM datastage tool is used to deploy job control.

17. How to do DataStage job performance tuning?

First, we choose the right configuration files, partition, and buffer memory. We take care of data sorting and handling null-time values. We should try to use copy, modify or filter rather than the transformer. The propagation of unnecessary metadata between stages needs to be reduced. 

18. What is a repository table in DataStage?

A repository table or data warehouse is used for answering ad-hoc, historical, analytical, or complex queries. A repository can be centralized or distributed. 

FREE Data Science With Python Course

Start Learning Data Science with Python for FREEStart Learning
FREE Data Science With Python Course

19. Another frequntly asked datastage interview questions is how can you kill a DataStage job?

We need to first kill the individual processing ID such that the DataStage is killed. 

20. Compare Validated OK with Compiled Process in DataStage.

The Validated OK process ensures that the connections are valid, whereas the Compiled process makes sure that important stage parameters are correctly mapped so that it creates an executable job. 

21. Explain Datatype conversion in DataStage.

We can use data conversion function for datatype conversion in DataStage. We must make sure that the input or the output to and from the operator is the same. Plus, the record schema must be compatible with the operator. 

22. What is an exception activity?

If there is an unfamiliar error occurring during the execution of the job sequencer, all the stages following the exception activity are executed. Hence, exception activity is very important in DataStage. 

23. Describe DataStage architecture briefly.

The DataStage architecture follows a client-server model with different architecture types for different versions. The main components of the model are:

Client components

Servers

Jobs

Stages

Projects

Table Definitions

Containers

Advanced DataStage Interview Questions

24. What are the command line functions that can help to import and export DS jobs?

The dsimport.exe is used to import DS jobs, and the dsexport.exe is used for export. 

25. Name the different types of lookups in DataStage.

There are normal, sparse, range, and caseless lookups. 

26. How do you run a job using command line?

This is how we run a job using command line:

dsjob -run -jobstatus <projectname> <jobname>

27. What is Usage Analysis?

To check if a certain job is part of the sequence, we right click on the manager on the job and select Usage Analysis.

28. Another frequntly asked datastage interview questions is what is the difference between sequential file and hash file?

A hash file, being based on hash algorithm, can be used with a key value. However, a sequential file does not have any key value column. 

Hash file can be used as lookup reference while sequential file cannot be used for lookup. It is easier to search hash file due to presence of hash key. 

Data Scientist Master's Program

In Collaboration with IBMExplore Course
Data Scientist Master's Program

29. How to clean a DataStage repository?

Go to DataStage Manager > Job in the menu bar > Clean up resources

For further removing the logs, go to respective jobs and clean up log files.

30. What does NLS mean?

NLS stands for National Language Support. It means we can use the DataStage tool in several languages like multi-byte character languages (Chinese, Japanese, Spanish). It is possible to read or write in any language. 

31. How can you drop the index prior to loading data in target in DataStage?

This is possible by using Direct Load functionality of SQL Loader Utility (sqlldr).

32. Which third party tools can be used in DataStage?

Autosys, TNG, and Event Coordinator are some third-party tools that can be used in DS.

33. What is a Hive connector?

A Hive connector is a tool that supports partition mode (modulus partition mode or maximum-maximum partition mode) while reading data. 

Are you considering a profession in the field of Data Science? Then get certified with the Data Science Bootcamp Program today!

If you’re interested to learn more about data science, consider enrolling for our top-ranked Data Scientist Course from Simplilearn – the world’s no. 1 online Bootcamp.                                                                                                  

About the Author

SimplilearnSimplilearn

Simplilearn is one of the world’s leading providers of online training for Digital Marketing, Cloud Computing, Project Management, Data Science, IT, Software Development, and many other emerging technologies.

View More
  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.