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I am an experienced Informatica Developer with expertise in ETL processes, data integration, and data warehousing.
Developing ETL mappings using Informatica PowerCenter
Designing and implementing data integration solutions
Optimizing performance of ETL processes
Troubleshooting and resolving data quality issues
Collaborating with business analysts and stakeholders to gather requirements
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 calculations and manipulating data
Filter transformation for filtering out unwanted data
Joiner transformation for joining data from multiple sources
Lookup transformation for retrieving...
Sorter can be active or inactive depending on the configuration.
Sorter transformation can be configured to be active or passive.
If active, it sorts the data based on specified criteria.
If passive, it passes the data through without sorting.
Sorter can be used to remove duplicates from data.
Sorter can also be used to sort data in ascending or descending order.
Update strategy is a transformation used to flag rows for insert, update, delete or reject.
Update strategy is used to control the flow of data in a mapping.
It is used to flag rows for insert, update, delete or reject.
It can be used to update a target table based on a source table.
It can be used to insert new rows into a target table.
It can be used to delete rows from a target table.
It can be used to reject rows that do
Caches are temporary storage areas that hold frequently accessed data for quick access.
There are several types of caches including CPU cache, disk cache, browser cache, and DNS cache.
CPU cache stores frequently accessed data from RAM for faster access.
Disk cache stores frequently accessed data from hard disk for faster access.
Browser cache stores frequently accessed web pages, images, and other resources for faster loa...
If we don't specify anything in group by aggregator, it will return the result without any grouping.
The result will contain all the rows from the input without any aggregation.
The output will have the same number of rows as the input.
No grouping will be performed on any column.
The output will be similar to a select statement without a group by clause.
I have a strong background in software engineering and a passion for innovation, making me a valuable asset to HSBC.
I have a proven track record of successfully delivering high-quality software solutions in previous roles.
I am highly skilled in various programming languages and technologies, including Java, Python, and SQL.
I have experience working in agile development environments, allowing me to adapt quickly to chan...
I applied via Naukri.com and was interviewed before Apr 2020. There were 3 interview rounds.
SCD Type 2 is a technique used to track historical changes in data over time in a data warehouse.
SCD Type 2 maintains a separate row for each change in data, with a start and end date.
It requires a surrogate key to uniquely identify each row.
Informatica provides a built-in SCD Type 2 transformation to implement this technique.
Example: tracking changes in customer addresses over time.
I applied via Campus Placement and was interviewed before Nov 2021. There were 3 interview rounds.
Moderate level aptitude with basics
Moderate level data structure questions
I applied via LinkedIn and was interviewed before Aug 2020. There were 3 interview rounds.
I applied via Recruitment Consultant and was interviewed in Dec 2020. There was 1 interview round.
I applied via Campus Placement and was interviewed before Sep 2020. There were 5 interview rounds.
I applied via Recruitment Consultant and was interviewed in May 2021. There was 1 interview round.
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Wells Fargo
JPMorgan Chase & Co.
HSBC Group
Cholamandalam Investment & Finance