AGIO Pharmaceuticals Interview Questions and Answers

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 data warehousing scenarios.

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 access control lists (ACLs).

• Gen2 allows direct access to data ...read more

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 consideration of the order.

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 databases include banking systems and e-commerce websites

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

• Dataframe supports SQL queries while RDD does not