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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;
I applied via Recruitment Consulltant and was interviewed in May 2024. There were 2 interview rounds.
SQL Scripts to write and also also asked to design an data model of my choice in Telecom Domain
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
I applied via Walk-in and was interviewed in May 2024. There was 1 interview round.
I applied via Company Website and was interviewed in Apr 2024. There were 3 interview rounds.
Test your algorithmic thinking and problem solving skills
I applied via Naukri.com and was interviewed in Nov 2023. There was 1 interview round.
posted on 17 Jan 2024
I applied via Job Portal
I applied via Naukri.com and was interviewed in Aug 2023. There were 2 interview rounds.
Activity lifecycle refers to the series of states an activity goes through during its lifetime in an Android app.
Activity is created with onCreate() method
Activity is started with onStart() method
Activity is resumed with onResume() method
Activity is paused with onPause() method
Activity is stopped with onStop() method
Activity is destroyed with onDestroy() method
Data binding is a technique in software development that establishes a connection between the UI components and the data sources.
Data binding allows for automatic synchronization of data between the UI and data sources.
It reduces boilerplate code by eliminating the need for manual updates to the UI when data changes.
Data binding can be implemented using frameworks like Android Data Binding Library.
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