Top 20 ETL Interview Questions and Answers

Implementing strategies to prevent data loss in ETL pipelines is crucial for data integrity and reliability.

• Implement data validation checks at each stage of the ETL process to ensure data integrity.

• Use logging mechanisms to track data flow and ident...read more

ETL is required to extract, transform and load data from various sources into a target system.

• ETL helps to integrate data from multiple sources into a single system

• It ensures data accuracy, consistency and completeness

• ETL is used in data warehousing,...read more

ETL and ELT tools are used for extracting, transforming, and loading data in data warehousing and analytics processes.

• ETL stands for Extract, Transform, Load and involves extracting data from various sources, transforming it into a usable format, and...read more

Data retrieval steps in Informatica ETL process

• Identify the source data to be extracted

• Create source and target connections in Informatica

• Design mappings to extract, transform, and load data

• Use transformations like Filter, Joiner, Lookup, etc.

• Run the...read more

A group in transformation refers to a collection of individuals or entities undergoing a process of change or development.

• A group in transformation involves a collective effort towards achieving a common goal.

• It often involves a shift in mindset, beh...read more

ETL stands for Extract, Transform, Load in SQL. It is a process of extracting data from various sources, transforming it into a usable format, and loading it into a target database.

• Extract: Retrieving data from different sources such as databases, fi...read more

The option 'Ignore Case' is good when using table comparison transformation.

• Use 'Ignore Case' option when comparing text values to ignore differences in case.

• This option is helpful when comparing strings like names or addresses.

• It ensures that 'John'...read more

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.

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 tar...read more

There are several ways to read external data, such as using file input/output operations, database queries, web scraping, and API calls.

• File input/output operations: Reading data from files stored on the local system or network.

• Database queries: Retr...read more

Comparing 2 flat files in GDE involves using the Join component and specifying the keys to match.

• Use the Join component in GDE to compare 2 flat files

• Specify the keys to match in the Join component

• Choose the type of join (inner, outer, left, right) b...read more

I have worked on AWS Glue, AWS Data Pipeline, and AWS Lambda for ETL processes.

• AWS Glue for serverless ETL jobs

• AWS Data Pipeline for scheduling and orchestrating ETL workflows

• AWS Lambda for building custom ETL functions

There are three types of LKM used in file to file loads: LKM File to SQL, LKM SQL to File, and LKM File to File.

• LKM File to SQL is used to load data from a file to a SQL database

• LKM SQL to File is used to extract data from a SQL database to a file

• LKM...read more

I have worked on various types of transformations including Aggregator, Expression, Filter, Joiner, Lookup, Router, and Sorter.

• Aggregator transformation for performing calculations on groups of data

• Expression transformation for performing calculation...read more

Designing architecture for ETL involves identifying data sources, transformation processes, and target destinations.

• Identify data sources such as databases, files, APIs

• Design data transformation processes using tools like Apache Spark, Talend

• Implemen...read more

Set up ETL flow for data in Lake House using Databricks

• Connect Databricks to Lake House storage (e.g. Azure Data Lake Storage)

• Define ETL process using Databricks notebooks or jobs

• Extract data from Lake House, transform as needed, and load into target...read more

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

• ETL involves extracting data from s...read more

ETL focuses on extracting, transforming, and loading data in a sequential process, while ELT involves loading data into a target system first and then performing transformations.

• ETL: Extract, Transform, Load - data is extracted from the source, trans...read more

ETL stands for Extract, Transform, Load. It is a process of extracting data from various sources, transforming it into a usable format, and loading it into a target database.

• ETL tools include Informatica PowerCenter, Talend, Apache Nifi, Microsoft SQ...read more

To perform a full load in SSIS, you can use the Data Flow Task with a source and destination component.

• Create a Data Flow Task in the Control Flow tab of the SSIS package.

• Add a source component to extract data from the source system.

• Add a destination...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...read more

ETL is a process of extracting data from various sources, transforming it and loading it into a target system. ELT is a process of extracting data from various sources, loading it into a target system and then transforming it.

• ETL involves transformin...read more

ETL is better for batch processing, ELT is better for real-time processing.

• ETL is better for large volumes of data that need to be transformed before loading into a data warehouse.

• ELT is better for real-time processing where data can be loaded into a...read more

Types of data ETL include batch processing, real-time processing, and change data capture.

• Batch processing involves processing data in large chunks at scheduled intervals.

• Real-time processing involves processing data as it is generated.

• Change data ca...read more

ETL architecture involves three main components: extraction, transformation, and loading.

• Extraction involves retrieving data from various sources such as databases, files, and APIs.

• Transformation involves cleaning, filtering, and converting the data ...read more

Different stages in ETL include extraction, transformation, and loading of data.

• Extraction: Retrieving data from various sources such as databases, files, APIs, etc.

• Transformation: Cleaning, filtering, and converting the extracted data into a format ...read more