DataStage is an ETL tool that is used in graphical notation to build solutions to data integration. The available versions of DataStage are SE (Server Edition), EE (Enterprise Edition), MVS (Multiple Virtual Storage) editions. The job role in DataStage comprises the knowledge of data warehouse, ETL, data storage, configuration, design, various stages, and modules in data stages. DataStage is used to integrate various systems (multiple systems) and processes high volumes of data. The popularity of DataStage is because of the user-friendly graphical front-end to design jobs.
The following write-up is written to make you aware of the DataStage interview questions and answers. It will be helpful in cracking foundation interview levels of DataStage-related jobs. Nonetheless, DataStage's real-time interview questions will help to get shortlisted for a job position.
Most frequently asked Datastage Interview Questions
Let’s begin with IBM DataStage Interview questions and answers.
Ans: DataStage is a tool developed by IBM that is used to design, develop, and execute different applications to fill the gap of multiple tables in data warehouses or data marts. It is software for windows servers that helps in data extraction from databases and modifies them into data warehouses. DataStage is an important part of the IBM WebSphere Data Integration Suite.
Ans: The types of stages are:
Ans: DataStage has a number of client and server components. It has four main components, namely:
Ans: Server Jobs work in a sequential way while parallel jobs work in a parallel fashion (Parallel Extender works on the principle of pipeline and partition) for I/O processing.
Ans: DataStage stores its repository in IBM Universe Database.
Ans: DataStage tool can be used by
Ans: Data about data is known as metadata. A table definition describing the structure of the table is known as metadata.
Ans: A stage that extracts data from or loads data into a Universe database using SQL. It is used to represent a data source, an aggregation step, or a target data table.
Ans: Dynamic arrays map the structure of DataStage file records to character string data. Any character string can be a dynamic array. A dynamic array is a character string containing elements that are substrings separated by delimiters.
DataStage has two types of containers - Local Container and Shared Container
|Do you want to master DataStage? Then enroll in "DataStage Training" This course will help you to master DataStage|
Ans: Hash file stage is a binary file used for lookup, for better performance.
Ans: Staging variables are the temporary variables created in the transformer for calculation.
Ans: The conversion of columns into rows can be done in DataStage utilizing the pivot stage.
Ans: The Merge stage combines a sorted master data set with one or more sorted update data sets. The columns from the records in the master and update data sets are merged so that the output record contains all the columns from the master record plus any additional columns from each update record.
Ans: A repository is a central store that contains all the information required to build a data mart or data warehouse.
Ans: A DataStage server runs executable jobs that extract, transform, and load data into a data warehouse.
Ans: A data warehousing strategy has the following advantages :
Capitalizes on the potential value of the organization’s information.
Improves the quality and accessibility of data.
Combines valuable archive data with the latest data in operational sources.
Increases the amount of information available to users.
Reduces the requirement of users to access operational data.
Reduces the strain on IT departments, as they can produce one database to serve all user groups.
Allows new reports and studies to be introduced without disrupting operational systems.
Promotes users to be self-sufficient.
Ans: Local Container is local to the particular job in which we have developed the container and Shared Container can be used in any other jobs.
Ans: OraBulk stage is used to Bulk Load the Oracle Target Database. By storing data at the OraBulk stage of DataStage means your data is stored at the Oracle Target Database.
Ans: The passive Stage is used for data extraction and loading
Active Stage is used to implement and process the business rules
|Related Article: DataStage Tutorials|
Ans: MetaData is data about the data. It contains-
Business subject area
Source to target mapping Information
Ans: The join stage is used to perform join operations on one or more data sets the input to the stage and then outputs the resulting dataset.
The merge stage is used to combine a sorted master data set with one or more sorted updated data sets. The columns from the records in the master and update data sets arc merged so that the output record contains all the columns from the master record plus any additional columns from each update record that required.
Ans: The default cache size in DataStage is 256 mb.
Ans: The components in DataStage can be reused by using shared and local containers.
Ans: DataStage provides us with the capability to eliminate duplicate rows in EE (Enterprise Edition) only. Using EE of DataStage, the elimination of duplicate rows can be done based on a key column.
Ans: dsimport.exe command-line function is used to import the DataStage components
dsexport.exe command-line function is used to export the DataStage components
|Also read, Related Article: Head Tail and Sample in DataStage|
Ans: Once during my project, I have used conditional scheduling. Using Sequencer Job we can create conditional scheduling.
Ans: Validating, Scheduling, Executing, and Monitoring Jobs (server Jobs).
Ans: A Hash file saves data on a hash algorithm and on a hash key value, while a sequential file doesn’t have any key value to save the data. Based on this hash key feature, searching in a Hash file is faster than in a sequential file.
Ans: NLS is referred to as National Language Support
Ans: The integrity stage is also known as the quality stage that helps in assistance in integrating various types of data from different sources.
Ans: In Datastage, OConv () and IConv() functions are used to convert formats from one format to another i.e. conversions of time, roman numbers, radix, date, numeral ASCII etc. IConv () is mostly used to change formats for the system to understand. While, OConv () is used to change formats for users to understand.
Ans: The BCP stage is used to store a big amount of data in one target table of Microsoft SQL Server.
Ans: In Datastage, Link Partitioner is used to split data into various parts by certain partitioning methods. Link Collector is used to collecting data from many partitions to a single data and save it in the target table.
Ans: Datastage is a tool from ETL (Extract, Transform and Load) and DataStage TX is a tool from EAI (Enterprise Application Integration).
Ans: In Datastage, Surrogate Key is used instead of a unique key. Surrogate key is mostly used for retrieving data faster. It uses Index to perform the retrieval operation. Surrogate key is a 4-byte integer that replaces the transaction/business / OLTP key in the dimension table. We can store up to 2 billion records.
The need for the Surrogate key is for integrating the data may help better for the primary key. Additionally, it is used for index maintenance, joins, table size, key updates, disconnected inserts and partitioning.
Ans: Constraints are expressions and you can specify a constraint for each output link from a transformer stage. You can also specify that a particular link is to act as an otherwise link and catch those rows that have failed to satisfy the constraints on all other output links.
Select an output link and click the constraints button
Double-click the output link's constraint entry field
Choose Constraints from the background or header shortcut menus
A dialogue box will appear which allows you either to define constraints for any of the transformer output links or to define a link as an otherwise link
[Check Out: String Functions in DataStage]
Ans: DataStage has three main components:
|Explore: Sorting Techniques in DataStage|
Ans: They are built from DataStage functions and do not require arguments. A number of macros are provided in the JOBCONTROL.H file to facilitate getting information about the current job, and links and stages belonging to the current job. These can be used in expressions (for example for use in Transformer stages), job control routines, filenames and table names, and before/after subroutines.
Ans: In DataStage, a conformed dimension is a dimension that has the same meaning to every fact with what it relates. It can exist as a single dimension table that relates to multiple fact tables within the same data warehouse, or as identical dimension tables in separate data marts.
Ans: Validating a job is all about running the job in ‘Check only’ mode.
The checks that will perform are
The compilation is done by
Let us now give a quick view at a few of the real-time DataStage interview questions that are asked in various MNC Companies Interviews. You might get many of the answers in the above questions and answers area but many of them are scenario-based DataStage question & answers that depend upon your logic and knowledge of DataStage.
The above write up is written to give a glance at DataStage production support interview questions. I hope the above write up will help you in gaining your dream job in DataStage!
You liked the article?
Like : 0
Vote for difficulty
Current difficulty (Avg): Medium
TekSlate is the best online training provider in delivering world-class IT skills to individuals and corporates from all parts of the globe. We are proven experts in accumulating every need of an IT skills upgrade aspirant and have delivered excellent services. We aim to bring you all the essentials to learn and master new technologies in the market with our articles, blogs, and videos. Build your career success with us, enhancing most in-demand skills in the market.
Get stories of change makers and innovators from the startup ecosystem in your inbox