50+ ETL Developer Interview Questions and Answers

APT_CONFIG_FILE is a configuration file used by Advanced Package Tool (APT) to manage packages in Linux.

• APT_CONFIG_FILE contains settings for APT such as proxy settings, package sources, and authentication credentials.

• Partition refers to dividing a hard drive into separate sections for different purposes.

• APT_CONFIG_FILE can be used to specify package sources for specific partitions.

• For example, if a user has a separate partition for development packages, they can specify the ...read more

RCP stands for Rich Client Platform. It is a framework used for developing desktop applications.

• RCP is based on Eclipse platform and provides a set of reusable components for building desktop applications.

• It provides a modular architecture that allows developers to easily add or remove features.

• RCP applications can be customized using plug-ins and extensions.

• I have used RCP in a project where we needed to develop a desktop application for data analysis and visualization.

• We us...read more

A trigger is a special type of stored procedure that automatically executes in response to certain events.

• Triggers are used to enforce business rules or to perform complex calculations.

• There are two types of triggers: DML triggers and DDL triggers.

• DML triggers fire in response to DML events (INSERT, UPDATE, DELETE).

• DDL triggers fire in response to DDL events (CREATE, ALTER, DROP).

• Triggers can be used to audit changes to data, enforce referential integrity, or perform custom v...read more

Aggregator stage methods include count, sum, average, min, max, first, last, and concatenate.

• Count: counts the number of input rows

• Sum: calculates the sum of a specified column

• Average: calculates the average of a specified column

• Min: finds the minimum value of a specified column

• Max: finds the maximum value of a specified column

• First: returns the first row of the input

• Last: returns the last row of the input

• Concatenate: concatenates the values of a specified column

Dimensional modeling factors include business requirements, data granularity, and data integration.

• Identify business requirements for the data warehouse

• Determine the level of data granularity needed for analysis

• Ensure data integration across multiple sources

• Choose appropriate dimensions and hierarchies

• Consider performance and scalability

• Examples: time, geography, product, customer

I have never crossed project deadlines in my career as an ETL Developer.

• I have always been proactive in managing my time and resources to ensure timely completion of projects.

• I prioritize tasks and create a detailed project plan to track progress and meet deadlines.

• I communicate effectively with stakeholders to manage expectations and address any potential delays.

• I have successfully completed multiple projects within the given timelines.

• I continuously monitor project progress...read more

SCD Type 2 is used to maintain historical data in a dimension table.

• SCD Type 2 is used to track changes in dimension attributes over time.

• It creates a new record for each change and maintains a history of all changes.

• It includes additional columns like start date, end date, and version number.

• Example: Employee table with changes in job title, salary, and department over time.

• It helps in analyzing trends and making informed decisions based on historical data.

Excel formulas can be used to calculate statistics and analyze data.

• Use SUM function to calculate total sum of a range of cells.

• Use AVERAGE function to find the average of a range of cells.

• Use COUNT function to count the number of cells that contain numbers in a range.

• Use MAX and MIN functions to find the maximum and minimum values in a range.

• Use IF function to perform conditional calculations based on certain criteria.

Python function to process data

• Define a function that takes in the data as input

• Process the data using Python code

• Return the processed data

Informatica Powercentre is an on-premise ETL tool, while iics is a cloud-based ETL tool.

• Informatica Powercentre is an on-premise ETL tool, meaning it is installed and run on the user's own hardware and infrastructure.

• iics (Informatica Intelligent Cloud Services) is a cloud-based ETL tool, allowing users to access and use the tool via the internet.

• Informatica Powercentre requires manual upgrades and maintenance, while iics is automatically updated by Informatica.

• Informatica Po...read more

Yes, I have created a complex SSIS package for loading data from multiple sources into a data warehouse.

• The SSIS package involved extracting data from various sources such as SQL Server, Excel files, and flat files.

• I used data flow tasks, conditional split transformations, and lookup transformations to cleanse and transform the data before loading it into the data warehouse.

• I implemented error handling and logging mechanisms to ensure the reliability and traceability of the d...read more

Type 2 SCD is used to track historical changes in data, creating new records for each change.

• In our project, we use Type 2 SCD to track changes in customer information such as address, phone number, and email.

• When a customer's address changes, a new record is created with the updated address and a new surrogate key.

• This allows us to maintain a history of customer information and analyze trends over time.

Pragma is used to provide instructions to the compiler, temporary table is a table that exists temporarily, SP is a stored procedure, cursor is used to iterate through a result set, finding second highest salary involves sorting the salaries in descending order and selecting the second row.

• Pragma is used to provide instructions to the compiler

• Temporary table is a table that exists temporarily

• SP stands for stored procedure

• Cursor is used to iterate through a result set

• To find t...read more

Difference between truncate, delete and drop

• Truncate removes all data from a table but keeps the structure

• Delete removes specific rows from a table

• Drop removes the entire table and its structure

• Truncate and drop cannot be rolled back, but delete can be

• Truncate is faster than delete as it does not log individual row deletions

Yes, I am open to taking on a testing project as part of my role as an ETL Developer.

• I have experience with testing tools and methodologies in my previous roles.

• I understand the importance of testing in ensuring data accuracy and quality.

• Taking on a testing project will help me improve my skills and knowledge in ETL development.

Records in a table can be deleted using SQL DELETE statement.

• Use the DELETE statement followed by the table name to delete records.

• You can add a WHERE clause to specify which records to delete.

• Make sure to commit the transaction after deleting records to make the changes permanent.

Filter stage is used in ETL processes to selectively pass or reject data based on specified criteria.

• Filter stage helps in removing unwanted data from the input dataset.

• It can be used to apply conditions like filtering out duplicate records, selecting specific columns, or excluding certain values.

• For example, a filter stage can be used to only pass records where the sales amount is greater than $1000.

Transform stage is used in ETL process to apply business rules, clean and enrich data before loading into target database.

• Transform stage is used to apply business rules to the data.

• It is used to clean and standardize data before loading into the target database.

• Transform stage can also be used to enrich data by combining multiple sources or adding calculated fields.

• Examples include converting data types, removing duplicates, and aggregating data.

Star schema has a centralized fact table with denormalized dimensions, while snowflake schema has normalized dimensions.

• Star schema is simpler and easier to understand compared to snowflake schema.

• In star schema, dimensions are denormalized and directly connected to the fact table.

• Snowflake schema has normalized dimensions, meaning dimensions are further broken down into sub-dimensions.

• Star schema is more suitable for data warehousing and reporting purposes.

• Snowflake schema i...read more

Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity.

• Normalization involves breaking down a table into smaller tables to reduce redundancy.

• It helps to avoid data inconsistencies and anomalies.

• Normalization is achieved through a series of normal forms, such as first normal form (1NF), second normal form (2NF), and so on.

• Each normal form has specific rules that must be followed to ensure data is properly organized.

• Normali...read more

Connected lookup is used in mapping to return multiple columns, while unconnected lookup is used in expressions to return a single value.

• Connected lookup is used in mapping to return multiple columns from a source, while unconnected lookup is used in expressions to return a single value.

• Connected lookup is connected directly to the source in the mapping, while unconnected lookup is called from an expression transformation.

• Connected lookup is faster as it caches the data, whil...read more

The greatest challenge faced during migration to cloud from on-premise DB is ensuring data security and compliance.

• Ensuring data security during transit and at rest

• Maintaining compliance with regulations and industry standards

• Minimizing downtime and ensuring data integrity

• Optimizing performance and cost efficiency in the cloud environment

I am using Talend version 7.3.1 for ETL development.

• I am currently using Talend version 7.3.1 for ETL development.

• The specific version of Talend being used is 7.3.1.

• Talend 7.3.1 offers various features and improvements for ETL processes.

Yes, I created a complex SSIS package to automate data migration between multiple databases.

• Used multiple data flow tasks to extract, transform, and load data

• Implemented error handling and logging to track data flow

• Utilized variables and expressions for dynamic behavior

• Included conditional logic for different data processing scenarios

ETL is Extract, Transform, Load where data is extracted, transformed, and loaded into a data warehouse. ELT is Extract, Load, Transform where data is extracted, loaded into a data warehouse, and then transformed.

• ETL involves extracting data from source systems, transforming it according to business rules, and loading it into a data warehouse.

• ELT involves extracting data from source systems, loading it into a data warehouse, and then transforming it as needed.

• ETL is suitable f...read more

To create a parallel job, use parallel processing techniques to divide tasks into smaller subtasks that can be executed simultaneously.

• Identify tasks that can be executed independently and in parallel

• Use parallel processing techniques such as multi-threading or distributed computing

• Implement parallel job using ETL tools like Informatica or Talend

• Monitor and optimize parallel job performance to ensure efficient execution

Sort stage is used in ETL processes to sort data based on specified criteria before loading it into the target system.

• Sort stage helps in arranging data in a specific order for better analysis and reporting

• It can be used to remove duplicates from data before loading

• Sorting can be done based on multiple columns or expressions

• Example: Sorting customer data based on their purchase amount before loading into a data warehouse

Linux permissions include read, write, execute, setuid, and setgid.

• Read permission allows a user to view the contents of a file or directory.

• Write permission allows a user to modify the contents of a file or directory.

• Execute permission allows a user to run a file or access the contents of a directory.

• Setuid permission allows a user to execute a file with the permissions of the file's owner.

• Setgid permission allows a user to execute a file with the permissions of the file's g...read more

ETL stands for Extract, Transform, Load while ELT stands for Extract, Load, Transform.

• ETL involves extracting data from source systems, transforming it, and then loading it into the target system.

• ELT involves extracting data from source systems, loading it into the target system, and then transforming it as needed.

• ETL is suitable for scenarios where data needs to be transformed before loading, while ELT is useful when raw data needs to be loaded first and then transformed.

• ETL...read more

Initial load in ETL refers to the process of loading data from source systems into the data warehouse for the first time.

• Initial load is typically a one-time process to populate the data warehouse with historical data.

• It involves extracting data from source systems, transforming it as needed, and loading it into the data warehouse.

• Initial load is often done using bulk loading techniques to efficiently transfer large volumes of data.

• It is important to carefully plan and execut...read more

For Each Loop Container is used to iterate through a set of objects or files in SSIS packages.

• Used to perform repetitive tasks on a set of objects or files

• Can be used to loop through files in a directory or rows in a table

• Requires a data source and a variable to store the current object or file

• Can be configured to run in parallel or sequentially

Mapping is the process of defining the relationship between source and target data in ETL.

• Mapping involves identifying the source and target data structures.

• It also involves defining the transformation rules to be applied to the source data.

• Mappings can be simple or complex depending on the complexity of the data.

• Mapping is a critical step in ETL as it determines the accuracy and completeness of the data in the target system.

Lookups are used to retrieve related data from another table based on a common key.

• Lookups are used in ETL processes to enrich data by adding additional information from a reference table.

• They are commonly used to replace codes with corresponding descriptions, such as replacing product IDs with product names.

• Lookups can be performed using SQL joins or lookup transformations in ETL tools like Informatica or Talend.

SCD Type 1 in IICS involves overwriting existing data with new data without maintaining historical changes.

• In IICS, use the Mapping Designer to create a mapping that loads data from source to target.

• Use a Lookup transformation to check if the record already exists in the target table.

• If the record exists, update the existing record with new data using an Update Strategy transformation.

• If the record does not exist, insert the new record into the target table.

• Ensure that the ma...read more

Rollback and commit are database transactions used to manage changes made to the database.

• Rollback is used to undo changes made in a transaction and restore the database to its previous state.

• Commit is used to save the changes made in a transaction permanently to the database.

• Rollback is typically used when an error occurs during a transaction, while commit is used when the transaction is successful.

• Example: If a transaction to transfer money from one account to another fails...read more

Use GROUP BY and HAVING clause to find duplicates in a table.

• Use GROUP BY to group rows with same values together

• Use HAVING COUNT(*) > 1 to filter out duplicates

• Example: SELECT column_name, COUNT(*) FROM table_name GROUP BY column_name HAVING COUNT(*) > 1;

Optimizing session involves tuning session settings, utilizing efficient data loading techniques, and minimizing resource usage.

• Tune session settings such as buffer size, commit interval, and block size for optimal performance

• Utilize efficient data loading techniques like bulk loading, incremental loading, and parallel processing

• Minimize resource usage by optimizing SQL queries, reducing unnecessary transformations, and utilizing caching mechanisms

Transactions are a set of operations that are executed as a single unit of work, ensuring data integrity and consistency.

• Transactions help maintain data integrity by ensuring all operations within the transaction are completed successfully or rolled back if any operation fails.

• Transactions follow the ACID properties - Atomicity, Consistency, Isolation, and Durability.

• Examples of transactions include transferring funds between bank accounts or booking a flight ticket where mul...read more

Session refers to a period of time during which a user interacts with a computer system or application.

• A session is created when a user logs into a system or application.

• It is used to track user activity and maintain user-specific data.

• Sessions can be terminated manually or automatically after a certain period of inactivity.

• Session management is important for security purposes.

• Examples of session management techniques include cookies and tokens.

Loads in Informatica refer to the process of moving data from source to target in a data warehouse.

• Loads involve extracting data from source systems

• Transforming the data as needed

• Loading the data into the target data warehouse or database

• Loads can be full, incremental, or delta depending on the requirements

• Example: Loading customer data from a CRM system into a data warehouse for analysis

Subscriptions in SSRS allow users to schedule and automate the delivery of reports via email or file share.

• Subscriptions can be set up to deliver reports at specific times or in response to data-driven events.

• Users can choose the delivery method (email, file share, etc.) and format (PDF, Excel, etc.) for the reports.

• Subscriptions can be managed and monitored through the SSRS web portal.

• Example: A user can set up a subscription to receive a sales report every Monday morning vi...read more

DTM error stands for Data Transformation Manager error, which occurs during the ETL process when there is an issue with data transformation.

• DTM error occurs during the ETL process when there is a problem with data transformation

• It can be caused by incorrect mapping of data fields, data type mismatches, or data quality issues

• DTM errors can lead to data loss, data corruption, or failed ETL processes

• Examples of DTM errors include transformation errors, data truncation errors, an...read more

Procedure uses are a way to group and organize a set of SQL statements into a reusable unit.

• Procedures can accept input parameters and return output parameters.

• They can be called from other SQL statements or applications.

• Procedures can help improve code reusability and maintainability.

• Examples: stored procedures in SQL Server, PL/SQL procedures in Oracle.

ETL process involves extracting data from various sources, transforming it to fit business needs, and loading it into a target database.

• Extract data from multiple sources such as databases, files, APIs, etc.

• Transform the data by cleaning, filtering, aggregating, and converting it to the desired format.

• Load the transformed data into a target database or data warehouse.

• ETL tools like Informatica, Talend, and SSIS are commonly used for this process.

Performance tuning of SSIS packages involves optimizing data flow, memory usage, and parallelism.

• Optimize data flow by using efficient data sources and destinations

• Minimize memory usage by using appropriate buffer sizes and reducing unnecessary data transformations

• Increase parallelism by using multiple threads and optimizing task execution order

• Use performance monitoring tools like SSIS logging and performance counters to identify bottlenecks

• Consider using advanced techniques...read more

Lookup is used in ETL processes to search for a specific value in a dataset and retrieve related information.

• Lookup is used to search for a specific value in a dataset

• It retrieves related information based on the search criteria

• Lookup can be used to join data from different sources based on a common key

There are three types of lookup transformations: Connected, Unconnected, and Cached.

• Connected lookup transformation is used to look up data from a relational table or view.

• Unconnected lookup transformation is used to look up data from a flat file or external source.

• Cached lookup transformation stores the lookup data in memory for faster access.