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Infosys Interview Questions and Answers

Updated 26 Sep 2024

Q1. Difference between where and having clause.

Ans.

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

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Q2. Different types of joins in SQL?

Ans.

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

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Q3. Tell me about SCD types with examples.

Ans.

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.

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Q4. What is junk dimension?

Ans.

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

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Q5. Snowflake Schema vs Star Schema

Ans.

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

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Q6. What is Control flow,data flow Types of transformation

Ans.

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.

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Q7. Types of LOD in tableau

Ans.

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

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Q8. Types of filter used

Ans.

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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