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IBM
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I applied via Naukri.com and was interviewed in Nov 2021. There were 4 interview rounds.
Flat file target loading process
Use Informatica PowerCenter to create a mapping
Define the source and target connections
Create a flat file target definition
Map the source fields to target fields
Configure the session properties
Run the workflow to load data into the flat file target
Router is an active transformation as it can change the number of rows that pass through it based on conditions.
Router transformation is used to route data from one source to multiple targets based on conditions.
It can change the number of rows that pass through it based on the conditions specified.
It evaluates each row against the conditions and sends the row to the appropriate output group.
It is an active transformat...
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Drop command deletes the table structure along with data, while truncate command deletes only the data.
Drop command removes the table structure and all its data, while truncate command only removes the data but keeps the table structure intact.
Drop command is a DDL (Data Definition Language) command, while truncate command is a DML (Data Manipulation Language) command.
Drop command is slower than truncate command as it ...
In my project, I perform validations such as data completeness, data accuracy, data transformation, and data integrity checks.
Data completeness checks to ensure all required fields are populated
Data accuracy checks to verify the correctness of data
Data transformation checks to validate the transformation rules are applied correctly
Data integrity checks to maintain data consistency and reliability
Star Schema is a type of database schema where a central fact table is connected to multiple dimension tables. Snowflake Schema is a normalized form of Star Schema where dimension tables are further normalized into sub-dimension tables.
Star Schema has a central fact table connected to multiple dimension tables
Snowflake Schema is a normalized form of Star Schema with sub-dimension tables
Star Schema is denormalized for b...
Fact tables contain quantitative data while dimension tables contain descriptive attributes.
Fact tables store measurable, quantitative data such as sales revenue or quantity sold
Dimension tables store descriptive attributes related to the data in the fact table, such as product name or customer details
Fact tables are typically normalized while dimension tables are denormalized for easier querying
Example: In a sales dat...
I applied via Naukri.com and was interviewed in Aug 2024. There was 1 interview round.
Project architecture refers to the overall structure of a software project, including components, modules, and their interactions.
Project architecture defines how different components of a software project are organized and interact with each other.
It includes the high-level design of the system, such as the database structure, data flow, and integration points.
Project architecture also involves decisions on technologi...
Challenges in ETL testing include data quality issues, complex transformations, and handling large volumes of data.
Data quality issues such as missing or incorrect data can impact testing results
Complex transformations can be difficult to validate and may lead to errors in the ETL process
Handling large volumes of data can slow down testing processes and require efficient testing strategies
Roles and responsibilities refer to the tasks and duties assigned to an individual within a specific job or position.
Roles define the position or job title of an individual within an organization.
Responsibilities outline the specific tasks, duties, and expectations associated with that role.
Roles and responsibilities help clarify expectations, define boundaries, and ensure accountability.
Examples include testing data e...
Use a dictionary to find duplicate values in an array of strings in Python.
Create an empty dictionary to store the count of each string in the array.
Iterate through the array and for each string, check if it exists in the dictionary. If it does, increment the count. If not, add it to the dictionary with a count of 1.
After iterating through the array, check the dictionary for any strings with a count greater than 1. The
I applied via Naukri.com and was interviewed in Jul 2024. There were 2 interview rounds.
Use OFFSET and FETCH in SQL to retrieve specific records from a table.
Use OFFSET to skip the first n-1 records
Use FETCH to limit the number of records to be retrieved
Example: SELECT * FROM table_name OFFSET 4 ROWS FETCH NEXT 5 ROWS ONLY
Constraints are rules or conditions that must be followed in order to ensure data integrity and accuracy.
Constraints define the limits or restrictions on data values in a database table
Examples of constraints include primary key, foreign key, unique key, and check constraints
Constraints help maintain data quality and consistency in a database
Low, Medium, and High priority defects are categorized based on their impact on the system and urgency of fixing.
Low priority defects are minor issues that do not significantly impact the system's functionality.
Medium priority defects are issues that have a noticeable impact on the system but are not critical.
High priority defects are critical issues that severely impact the system's functionality and need immediate at...
Joins are used to combine rows from two or more tables based on a related column between them.
Joins are used in SQL to retrieve data from multiple tables based on a related column.
Common types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column;
A domain name from an email refers to the part after the @ symbol in an email address.
The domain name is typically the name of the organization or service provider associated with the email address.
For example, in the email address example@gmail.com, 'gmail.com' is the domain name.
dense_rank() assigns a unique rank to each distinct row, row_number() assigns a unique sequential integer to each row.
dense_rank() is used to assign a unique rank to each distinct row based on the specified order.
row_number() is used to assign a unique sequential integer to each row in the result set.
Example: dense_rank() - SELECT dense_rank() OVER (ORDER BY salary) AS rank FROM employees;
Example: row_number() - SELECT...
SCD types refer to slowly changing dimensions in data warehousing. Star schema is denormalized while snowflake schema is normalized.
SCD types refer to how dimensions change over time in a data warehouse
Type 1: Overwrite existing data with new data
Type 2: Keep track of historical data with new records
Type 3: Keep track of some historical data with limited history
Star schema is denormalized with a central fact table conn...
Group by clause is used in SQL to group rows that have the same values into summary rows.
Group by clause is used with aggregate functions like SUM, COUNT, AVG, etc.
It is used to group rows based on one or more columns specified in the query.
Group by clause must be used after the WHERE clause and before the ORDER BY clause.
Example: SELECT department, COUNT(*) FROM employees GROUP BY department;
Seeking new challenges and growth opportunities in a different environment.
Desire for career advancement
Interest in learning new technologies
Seeking a more challenging role
Company restructuring or downsizing
Relocation to a different city
My strengths include attention to detail and problem-solving skills. My weakness is sometimes being too critical of my own work.
Strength: Attention to detail - I always ensure that all aspects of the testing process are thoroughly checked.
Strength: Problem-solving skills - I am able to quickly identify and resolve issues that arise during testing.
Weakness: Being too critical of my own work - I sometimes spend too much
I applied via Naukri.com and was interviewed in Nov 2024. There was 1 interview round.
ETL Developers are responsible for designing, developing, and maintaining ETL processes to extract, transform, and load data from various sources into a data warehouse.
Designing ETL processes to extract data from multiple sources
Transforming data to meet business requirements
Loading data into a data warehouse or other target systems
Developing and maintaining ETL jobs using tools like Informatica, Talend, or SSIS
SCD Type 1 in IICS involves overwriting existing data with new data without maintaining historical changes.
In IICS, use the Mapping Designer to create a mapping that loads data from source to target.
Use a Lookup transformation to check if the record already exists in the target table.
If the record exists, update the existing record with new data using an Update Strategy transformation.
If the record does not exist, inse...
Entry criteria and exit criteria are conditions that must be met before and after testing, respectively.
Entry criteria are the conditions that must be fulfilled before testing can begin
Exit criteria are the conditions that must be fulfilled before testing can be considered complete
Entry criteria can include having test data ready, test environment set up, and test cases prepared
Exit criteria can include all test cases ...
Filter source data by department id and store in unique files
Use Talend components like tFilterRow to filter data based on department id
Create a unique file for each department using tFileOutputDelimited component
Loop through all department ids to process data for each department
Optimizing SQL queries can improve query performance by using indexes, avoiding unnecessary joins, and optimizing the query structure.
Use indexes on columns frequently used in WHERE clauses
Avoid using SELECT * and only retrieve necessary columns
Optimize joins by using INNER JOIN instead of OUTER JOIN when possible
Use WHERE clause to filter data early in the query
Avoid using functions in WHERE clauses as they can preven
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
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