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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 applied via Campus Placement and was interviewed before Jan 2022. There were 4 interview rounds.
It's an assignment for apti, verbal
I applied via Campus Placement and was interviewed before Oct 2023. There was 1 interview round.
I applied via Campus Placement and was interviewed before Aug 2022. There were 3 interview rounds.
2 coding questions, 1 hr and Aptitude questions are also clubbed into other section.
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.
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.
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...
I applied via Campus Placement and was interviewed before Feb 2023. There was 1 interview round.
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
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;
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