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I applied via Referral and was interviewed in May 2024. There was 1 interview round.
Polybase is a feature in Azure SQL Data Warehouse that allows users to query data stored in Hadoop or Azure Blob Storage.
Polybase enables users to access and query external data sources without moving the data into the database.
It provides a virtualization layer that allows SQL queries to seamlessly integrate with data stored in Hadoop or Azure Blob Storage.
Polybase can significantly improve query performance by levera...
Coding round will consists of SQL and pyspark questions, it's a medium level
I applied via Job Portal and was interviewed in Dec 2023. There was 1 interview round.
Data Lake Gen1 is based on Hadoop Distributed File System (HDFS) while Gen2 is built on Azure Blob Storage.
Data Lake Gen1 uses HDFS for storing data while Gen2 uses Azure Blob Storage.
Gen1 has a hierarchical file system while Gen2 has a flat file system.
Gen2 provides better performance, scalability, and security compared to Gen1.
Gen2 supports Azure Data Lake Storage features like tiering, lifecycle management, and acce...
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I was interviewed in Apr 2023.
Rank, dense rank, and row number are SQL functions used to assign a unique sequential number to rows in a result set.
Rank function assigns a unique number to each row based on the ordering specified in the query.
Dense rank function also assigns a unique number to each row, but it does not leave gaps in the ranking sequence.
Row number function simply assigns a sequential number to each row in the result set, without any
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I applied via Approached by Company and was interviewed in Jun 2022. There were 2 interview rounds.
It was a 1 hour technical assessment which includes azure questions
Copy activity in ADF is used to move data from source to destination.
Copy activity supports various sources and destinations such as Azure Blob Storage, Azure SQL Database, etc.
It can be used for both one-time and scheduled data movement.
It supports mapping data between source and destination using mapping data flows.
Slowly changing dimensions can be handled using copy activity in ADF.
Copy activity is commonly used in
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OLAP is for analytics and reporting while OLTP is for transaction processing.
OLAP stands for Online Analytical Processing
OLTP stands for Online Transaction Processing
OLAP is used for complex queries and data analysis
OLTP is used for real-time transaction processing
OLAP databases are read-intensive while OLTP databases are write-intensive
Examples of OLAP databases include data warehouses and data marts
Examples of OLTP d...
Dataframe is a distributed collection of data organized into named columns while RDD is a distributed collection of data organized into partitions.
Dataframe is immutable while RDD is mutable
Dataframe has a schema while RDD does not
Dataframe is optimized for structured and semi-structured data while RDD is optimized for unstructured data
Dataframe has better performance than RDD due to its optimized execution engine
Dataf
I applied via Recruitment Consulltant and was interviewed in Nov 2024. There was 1 interview round.
I applied via LinkedIn and was interviewed in Aug 2024. There were 2 interview rounds.
Medallion Architecture is a data processing architecture that involves breaking down data into smaller pieces for easier processing.
Medallion Architecture involves breaking down data into smaller pieces for easier processing
It allows for parallel processing of data to improve performance
Commonly used in big data processing systems like Hadoop and Spark
Spark Architecture is a distributed computing framework that provides an efficient way to process large datasets.
Spark Architecture consists of a driver program, cluster manager, and worker nodes.
It uses Resilient Distributed Datasets (RDDs) for fault-tolerant distributed data processing.
Spark supports various programming languages like Scala, Java, Python, and SQL.
It includes components like Spark Core, Spark SQL, Spa...
Use SQL query to find the second highest salary in employee table
Use SQL query with ORDER BY and LIMIT to get the second highest salary
Example: SELECT DISTINCT salary FROM employee ORDER BY salary DESC LIMIT 1, 1
Partitioning in Azure Data Engineer involves dividing data into smaller chunks for better performance and manageability.
Partitioning can be done based on a specific column or key in the dataset
It helps in distributing data across multiple nodes for parallel processing
Partitioning can improve query performance by reducing the amount of data that needs to be scanned
In Azure Synapse Analytics, you can use ROUND_ROBIN or H
As an Azure Data Engineer, my current responsibilities include designing and implementing data solutions on Azure, optimizing data storage and processing, and ensuring data security and compliance.
Designing and implementing data solutions on Azure
Optimizing data storage and processing for performance and cost efficiency
Ensuring data security and compliance with regulations
Collaborating with data scientists and analysts
Partition key is a field used to distribute data across multiple partitions in a database for scalability and performance.
Partition key determines the partition in which a row will be stored in a database.
It helps in distributing data evenly across multiple partitions to improve query performance.
Choosing the right partition key is crucial for efficient data storage and retrieval.
For example, in Azure Cosmos DB, partit...
Data bricks is a unified analytics platform for big data and machine learning, while ADF (Azure Data Factory) is a cloud-based data integration service.
Data bricks is a unified analytics platform that provides a collaborative environment for big data and machine learning projects.
ADF is a cloud-based data integration service that allows you to create, schedule, and manage data pipelines.
Data bricks supports multiple pr...
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