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I applied via Referral and was interviewed in Jul 2024. There was 1 interview round.
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.
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
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
I am an experienced ETL Developer with a strong background in data integration and transformation.
Over 5 years of experience in ETL development
Proficient in using tools like Informatica, Talend, and SSIS
Strong SQL skills for data querying and manipulation
Experience in designing and implementing data warehouses
Familiar with data modeling and ETL best practices
I applied via Campus Placement and was interviewed before Jan 2022. There were 4 interview rounds.
It's an assignment for apti, verbal
I was interviewed in Jun 2024.
I applied via LinkedIn and was interviewed in Aug 2022. There was 1 interview round.
I applied via Recruitment Consulltant and was interviewed in Feb 2024. There was 1 interview round.
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 dupl
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 warehou
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 executio
SCD stands for Slowly Changing Dimension, a technique used in data warehousing to track changes in dimension attributes over time.
SCD is used to maintain historical data in a data warehouse
There are different types of SCDs - Type 1, Type 2, and Type 3
Type 1 SCD overwrites old data with new data
Type 2 SCD creates a new record for each change and maintains history
Type 3 SCD keeps a limited history by adding columns to tr
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