Top 25 Datastage Interview Questions and Answers 2023

Datastage Interview Questions and Answers

It would be best to prepare adequately before stepping into an interview room. This article will look at some of the questions you should expect in a Datastage interview to help you land the job. Take a look at the following:

1. What Do You Understand by Datastage?

Datastage is a tool that designs, develops and executes several applications to fill several data tables in a data warehouse or mart. It usually obtains data from databases before converting them into data warehouses. It can also be defined as an ETL tool that extracts, transforms and apply business principles before loading them. It is, therefore, an essential part of the IBM WebSphere data integration suite.

2. Can You Explain the Difference Between Datastage and Informatica?

There are lots of differences between PowerCenter and Datastage. Datastage has a concept of parallelism and node configuration that lacks the latter. This is one of the most significant differences between these two. Also, Informatica is more scalable than Datastage. Scalability refers to the ability of a system to increase or decrease its performance in light of changes in application and system processing demands. Lastly, Datastage is more user-friendly than Informatica, which explains why it is more popular.

3. Can You Mention Some of the Steps that One Can use to Improve Datastage Jobs?

There are several steps that one can use to improve the performance of Datastage. The first is to establish the baseline, which offers a clear picture of all the hardware and software. Also, avoiding performance testing and working in increments usually works for Datastage Jobs. To fix any bottlenecks, one should isolate and solve the problems before distributing the file systems. While at it, one should also include RDBMS for the testing phase. Understanding and assessing the different tuning knobs is also necessary.

4. Can You Mention the Components of a Datastage Server?

There are three components of a DataStage server. These include the repository, Datastage server and Datastage package installer. The repository usually offers the information necessary for running and building every ETL job( extract, transform and load). On the other hand, the DataStage server runs jobs meant to transfer, load and extract data into separate warehouses. They store and manage databases on the server and offer only authorized users data access. Lastly, the Datastage package installer packages jobs and plugins.

5. Please Describe the Datastage Architecture

Datastage’s architecture is usually a client-server model, which means that it usually has several architectures for its versions. There are seven components of the client-server architecture, namely: stages, servers, jobs, projects, containers, table definitions and client components. It is worth noting that there are three types of stages, namely server job file stage, processing stage, dynamic relational stage and server job database stage. Containers group stages and connections, just like the name suggests. They, therefore, simplify and modularize job designs for servers, permitting the replacement of challenging diagram areas.

6. Can You Mention the Features of a Flow Designer

A flow designer has three main features. First, you don’t have to migrate the jobs to use the flow designer. Secondly, it helps to perform jobs with several stages, and lastly, it allows you to use the offered pallet for the removal and addition of different connectors and operators. This is usually permitted thanks to the drag and drop feature on the designer canvas. It is also worth mentioning that flow designers have five major components, namely conditions, triggers, flows, subflows and actions. All these play important purposes in Datastage.

7. Can You Tell Us the Different Types of Lookups in Datastage?

There are four different types of Lookups in Datastage. These are sparse, range, caseless and normal Lookups. The sparse lookup can only be found when the database stage is connected directly to a reference link.  There shouldn’t be any immediate stages. The range lookup, which is part of the lookup functionality, compares two fields on a lookup link using a between clause. In the normal lookup, the data must be in memory. However, it is worth noting that it usually results in poor performance for massive reference data.

8. Explain Usage Analysis in Datastage

Usage analysis in Datastage permits users to check the usage location of items in the Datastage repository. It usually shows a detailed list of all the items using a given source item. It also has the ability to offer a warning when a user tries to delete or change one of the items in the project, making it an essential aspect of the database. Therefore, the usage database helps users confirm if a given job is part of the sequence by right-clicking on the job manager and choosing the usage analysis.

9. Differentiate Between a Sequential and Hash File

Hash files are generally based on hash algorithms, meaning one can use them with a particular key value. On the other hand, sequential values do not contain key-value columns. Secondly, thanks to its constitution and source, the hash file can be used as a reference lookup, whereas a sequential file can’t be used as a lookup. Lastly, a hash file is easier to retrieve than a sequential file because of the presence of the hash key. Those are just a few differences that exist between the two.

10. What Do You Understand by a Conductor Node?

The conductor node is the primary process applied in starter jobs and determining source requirements. Every process on Datastage, therefore, has a conductor process. Here, the execution is generally in action and the section leader processes every processing node while the player deals with different combined operators. The individual player is in charge of processing all the uncombined operators in this process. To kill a process, one has to eliminate the player process before the section leader and conductor processes.

11. Can You Mention the Different Associations With the  ‘dsjob’ Commands

There are several options associated with the dsjob command. These include stop, which usually stops the running job, Ijobs, which unrolls all the jobs in the project, ilinks which lists the links, Iprojects listing the projects, Istages, which like the name suggests, lists all the present stages and projectinfo which generally offers the project information such as the hostname and project name. We also have the linkinfo, which returns the link information, Iparams listing the job parameters, paraminfo, which offers the parameters information, log, which adds a text message to the log and logsum displaying the log. These are a few options connected with dsjob.

12. Can You Tell Us the Benefits of a Flow Designer

A Flow designer has several benefits that related users should be aware of. First, it doesn’t make it mandatory to migrate jobs to a new location, thanks to its user interface. It also doesn’t require upgrading servers and buying virtualization technology licenses, saving users time and money. A flow designer also enhances continuous work since all your recent activities can show up in the job dashboard, allowing fast access to all your previous jobs. A flow designer also helps you efficiently search for jobs thanks to the inbuilt type-ahead search feature available in the jobs dashboard for all users. Lastly, one can store their preferences since the flow designer can automatically save viewing preferences across different sessions.

13. Do You Know the Capabilities of a Kafka Connector?

A Kafka connector has several abilities that any Datastage technician should know. First, it has a continuous mode permitting the consumption of incoming topic messages while the connector is still running. Secondly, a Kafka connector has transactions that allow several Kafka messages to be fetched within a given transaction. Once the record count has been achieved, the wave marker end goes to the output link. Lastly, a Kafka connector supports the Kerberos key tab.

14. What Do You Know About Data Partitioning?

The time I have spent in this field has informed me a lot about data partitioning. It is a parallelism approach that breaks data into different partitions or subsets, therefore, providing a linear increase in application performance. Users usually choose the data partitioning algorithm they want when designing a job. These include the modulus, range and hash, among many others. 

 15. Do You Know How to Combine Data in a Datastage Job?

There are two ways of combining data in an infosphere Datastage job that are usually applied in different circumstances. The first and most prominent are the lookup and join stages that conduct equivalent operations by combining multiple input datasets. Whenever sorting can’t happen, which occasionally occurs depending on the volume of the dataset, lookup is often preferred. The second way is the lookup stage which comes in handy whenever lookup stages are small and can fit in the available memory. It is worth mentioning that this stage requires everything to fit into the physical memory except the first input.

16. Can You Mention the Different Types of Parallel Processing

There are two types of parallel processing, namely data partitioning and data pipelining. Data pipelining extracts records from a data source system before transferring them through processing functions defined in the data flow. It is also worth mentioning that this is always defined in the job, and the records flowing in the pipeline can be quickly processed without writing them to the available disk. On the other hand, data partitioning refers to breaking down data or records into different partitions or records subsets.

17. You Have Mentioned Jobs a number of Times in this Interview. Can You Please Define Want They are?

Jobs are popular objects in Datastage. They refer to the different design objects and elements capable of connecting to a data source. Therefore, they can offer ETL functions such as extracting and transforming data before loading the records in a given target system. It is also worth pointing out that these design objects are generally created through a visual paradigm, which allows the right party to understand what the job plans to achieve.

18. Can You Mention the Different Tiers on the InfoSphere Information Server

There are four main tiers in the InfoSphere Information Server. These are client, engine, service and the metadata repository tier. The client tier contains the client programs and consoles and the computers where they are stored. It usually facilitates overall administration, development and a number of other tasks. The engine tier has the logical group of every engine component and communication agent, among many more. The engine is mandated with jobs and an array of tasks for product modules. Lastly, the metadata repository tier has a metadata repository and several database and database schemas when installed in a suite.

19. Can You Tell Us About The Service Tier in the Information Database?

The service tier is a collection of services that include the application server, the computer which holds all the components, product services for the given suite and product modules and the application server. Some of the common services, in this case, are metadata and logging. It is worth mentioning that the service tier offers common services and specific services, targeting different modules. The application server hosts the service in this tier while the tier hosts all the web-based InfoSphere application servers. All in all, the most important thing worth knowing in the service tier are its offerings.

20. Do You Know about the 7. x and 8. x Versions of Datastage? Can You Tell their Difference

There are several differences between these two main versions of Datastage. First, developers made the 7. x version platform-dependent, whereas the 8. x version is platform-independent. The former has a 2-tier architecture that supports building the Datastage on top of a Unix server, whereas the 8. x version has a 3-tier architecture. The Unix database is usually located below the XMETA database. Third, 7. x does not recognize parameters set while 8. x has versatile parameter sets. The designer and manager are two separate clients in 7. x while the manager and designer-client are on the 8. x version. Lastly, 7. x required people to manually search for jobs, whereas 8. x has a quick find option that supports a more accessible search function.

21. What are Some of the Features of the IBM InfoSphere Server Suite?

The IBM InfoSphere Server Suite has several features. First, it offers a single platform for data integration, meaning that it can connect to different source systems and access several target systems. Also, it runs on centralized layers. All the components are capable of sharing the suite’s baseline architecture. Third, the InfoSphere information server suite contains layers for its unified repository and offers different tools that help monitor, cleanse, and transform data. Lastly, it can excellently perform parallel processing.

22. You’ve Just Mentioned that the IBM Information Server Suite has Different Layers. Can You Mention Them?

There are five different layers in the IBM Information Server architecture. These are common services, common connectivity, unified metadata, unified parallel processing and unified user interface. To shed more light on a few of these, unified metadata refers to the technical infrastructure and data architecture components related to Datastage. The unified user interface allows easy access and operability by different users.

23. Can You Mention Some of the Services in Datastage

There are four different data services in Datastage: security, looping and reporting, unified service deployment, and metadata services. Metadata refers to the information about a given data. The security service allows for externalizing access policy decisions in different business transactions. All these perform essential functions in Datastage that every technician should know.

24. Can You Mention the Steps Required to Come Up With a Basic Datastage Job

There are a number of steps required to develop a simple basic DataStage job. First, you need to click on the file and then on ‘new’ before selecting a parallel job and hitting okay. A parallel job window will then come up, allowing you to piece different stages and define how data flows between them. This mainly works for an ETL job, which is the simplest DataStage job. You may also have to extract data from a database table or file to use in the file or database stage. When reading or extracting data from a text file, one should drag and drop the sequential file stage to the now opened Parallel job window.

25. Can You Mention the Different Sorting Methods in Datastage

Datastage allows users to insert a sort operation in several stage types of data inputs. There is a sorting option on the input page partitioning tab, which allows one to specify sorting keys. There are two different sorting methods in Datastage, namely link and inbuilt Datastage sort. One can use the link sort in several processing stages since it uses a scratch disk, giving it a physical location on the disk.


These twenty-five recommendations are some of the most common Datastage interview questions that you are likely to encounter in your interview. Take some time to go through them and work your posture, first impression and gestures.

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