IBM Data Analyst Intern Interview Questions and Answers

I have worked on various technologies including Hadoop, Spark, SQL, Python, and AWS.

• Experience with Hadoop and Spark for big data processing

• Proficient in SQL for data querying and manipulation

• Skilled in Python for data analysis and scripting

• Familiarity with AWS services such as S3, EC2, and EMR

• Knowledge of data warehousing and ETL processes

ADLS is Azure Data Lake Storage, a scalable and secure data lake solution in Azure.

• ADLS is designed for big data analytics workloads

• It supports Hadoop Distributed File System (HDFS) and Blob storage APIs

• It provides enterprise-grade security and compliance features

• To pass parameters from ADF to Databricks, use the 'Set Parameters' activity in ADF and reference them in Databricks notebooks

Spark has a master-slave architecture with a cluster manager and worker nodes.

• Spark has a driver program that communicates with a cluster manager to allocate resources and schedule tasks.

• The cluster manager can be standalone, Mesos, or YARN.

• Worker nodes execute tasks and store data in memory or on disk.

• Spark can also utilize external data sources like Hadoop Distributed File System (HDFS) or Amazon S3.

• Spark supports va...read more

Triggers in Azure are used to initiate an action based on a specific event or condition.

• Triggers can be used in Azure Functions to execute code in response to events such as changes in data or messages in a queue.

• Azure Logic Apps also use triggers to start workflows based on events such as receiving an email or a new file being added to a storage account.

• Triggers can be configured to run on a schedule or based on a spe...read more