Fractal Analytics Azure Data Engineer Interview Questions and Answers

Types of transformations include filtering, sorting, aggregating, joining, and pivoting.

• Filtering: Selecting a subset of rows based on certain criteria.

• Sorting: Arranging rows in a specific order based on one or more columns.

• Aggregating: Combining multiple rows into a single result, such as summing or averaging values.

• Joining: Combining data from multiple sources based on a common key.

• Pivoting: Restructuring data from ...read more

Spark is lazy execution to optimize performance by delaying computation until necessary.

• Spark delays execution until an action is called to optimize performance.

• This allows Spark to optimize the execution plan and minimize unnecessary computations.

• Lazy evaluation helps in reducing unnecessary data shuffling and processing.

• Example: Transformations like map, filter, and reduce are not executed until an action like collec...read more

SCD stands for Slowly Changing Dimension. There are three types: Type 1, Type 2, and Type 3.

• SCD is used in data warehousing to track changes in dimension data over time.

• Type 1 SCD overwrites old data with new data, losing historical information.

• Type 2 SCD creates new records for each change, preserving historical data.

• Type 3 SCD keeps both old and new data in the same record, with separate columns for each version.

A linked service is a connection to an external data source or destination in Azure Data Factory.

• Linked services define the connection information needed to connect to external data sources or destinations.

• They can be used in pipelines to read from or write to the linked data source.

• Examples of linked services include Azure Blob Storage, Azure SQL Database, and Salesforce.

• Linked services can store connection strings, a...read more

A dataset is a collection of data that is organized in a structured format for easy access and analysis.

• A dataset can consist of tables, files, or other types of data sources.

• It is used for storing and managing data for analysis and reporting purposes.

• Examples of datasets include customer information, sales data, and sensor readings.

• Datasets can be structured, semi-structured, or unstructured depending on the type of d...read more

Partition pruning is a query optimization technique that reduces the amount of data scanned by excluding irrelevant partitions.

• Partition pruning is used in partitioned tables to skip scanning partitions that do not contain data relevant to the query.

• It helps improve query performance by reducing the amount of data that needs to be processed.

• For example, if a query filters data based on a specific partition key, partiti...read more