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Infosys Interview Questions and Answers
Q1. Difference between where and having clause.
WHERE clause filters rows before grouping, while HAVING clause filters groups after grouping.
WHERE clause is used to filter rows based on a condition before grouping.
HAVING clause is used to filter groups based on a condition after grouping.
WHERE clause is used with SELECT, UPDATE, DELETE statements.
HAVING clause is used with GROUP BY clause.
WHERE clause cannot contain aggregate functions.
HAVING clause can contain aggregate functions.
Example: SELECT department, COUNT(*) FROM ...read more
Q2. Different types of joins in SQL?
Different types of joins in SQL include inner join, left join, right join, and full outer join.
Inner join returns only the matching rows from both tables
Left join returns all rows from the left table and matching rows from the right table
Right join returns all rows from the right table and matching rows from the left table
Full outer join returns all rows from both tables, with NULL values for non-matching rows
Q3. Tell me about SCD types with examples.
SCD types refer to slowly changing dimensions in data warehousing, categorized into Type 1, Type 2, and Type 3.
Type 1 SCD: Overwrites existing data with new information, losing historical data.
Type 2 SCD: Maintains historical data by creating new records for changes, with a surrogate key for each version.
Type 3 SCD: Keeps both old and new values in the same record, with separate columns for each version.
Q4. What is junk dimension?
A junk dimension is a single dimension table that combines multiple low-cardinality attributes that are not related to the fact table.
Contains attributes that are not related to the fact table
Reduces the number of dimension tables in the data warehouse
Helps in simplifying the data model and improving query performance
Q5. Snowflake Schema vs Star Schema
Snowflake schema is a normalized form of star schema with multiple levels of dimension tables.
Snowflake schema has normalized dimension tables, leading to reduced redundancy and improved data integrity.
Star schema has denormalized dimension tables, which can lead to data redundancy but faster query performance.
Snowflake schema is more complex to query compared to star schema due to multiple levels of normalization.
Star schema is simpler and easier to understand for end users ...read more
Q6. What is Control flow,data flow Types of transformation
Control flow and data flow are two important components of SSIS. There are various types of transformations available in SSIS.
Control flow is used to manage the flow of tasks and containers in a package.
Data flow is used to extract, transform, and load data from various sources to destinations.
Transformations are used to modify data during the ETL process. There are various types of transformations such as Aggregate, Derived Column, Lookup, Merge, etc.
Q7. Types of LOD in tableau
Types of LOD in Tableau include Fixed, Include, and Exclude.
Fixed LOD: Computes a value using a specific dimension without reference to the view level
Include LOD: Computes a value at a specified dimension level
Exclude LOD: Computes a value at a specified dimension level excluding the dimension specified
Q8. Types of filter used
Types of filters used in Tableau include extract filters, context filters, data source filters, and quick filters.
Extract filters are used to filter data before it is extracted into Tableau.
Context filters are used to filter data in a specific order, affecting subsequent filters.
Data source filters are applied at the data source level, affecting all workbooks and views using that data source.
Quick filters allow users to interactively filter data in a visualization.
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