Accenture Data Engineer Interview Questions, Process, and Tips

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Q1. Tell me about yourself
Ans. 
I am a data engineer with a strong background in programming and data analysis.
• Experienced in programming languages such as Python, SQL, and Java

• Skilled in data manipulation, ETL processes, and data visualization tools

• Worked on projects involving big data processing and machine learning algorithms
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Q2. Why do you want to join accenture
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I want to join Accenture because of their reputation for innovation and their focus on professional development.
• Accenture is known for its cutting-edge technology solutions and innovative approach to problem-solving

• I am impressed by Accenture's commitment to continuous learning and career growth opportunities

• I believe that joining Accenture will provide me with the chance to work on challenging projects and collaborate
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Q1. All sql related questions
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Q2. SCD in informatica
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Slowly Changing Dimension (SCD) in Informatica is used to track historical data changes in a data warehouse.
• SCD Type 1: Overwrite old data with new data

• SCD Type 2: Add new row for each change with effective start and end dates

• SCD Type 3: Add columns to track changes without adding new rows
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Q1. Salary expected
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Q2. Can join early?
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Q1. Azure tech stack used in the current project
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Azure tech stack used in the current project includes Azure Data Factory, Azure Databricks, and Azure SQL Database.
• Azure Data Factory for data integration and orchestration

• Azure Databricks for big data processing and analytics

• Azure SQL Database for storing and querying structured data
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Q2. Spark architecture
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Q1. How to create mount points
Ans. 
Mount points are directories in a Unix-like operating system where additional file systems can be attached.
• Use the 'mount' command to attach a file system to a directory

• Specify the device or file system to be mounted and the directory where it should be attached

• Use the 'umount' command to detach a file system from a directory
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Q2. ADF Activities and Flows
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Q1. Explain your project
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Q2. Sql interview questions
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Q1. What is an Accumulator
Ans. 
An accumulator is a variable used in distributed computing to aggregate values across multiple tasks or nodes.
• Accumulators are used in Spark to perform calculations in a distributed manner.

• They are read-only variables that can only be updated by an associative and commutative operation.

• Accumulators are used for tasks like counting elements or summing values in parallel processing.

• Example: counting the number of errors
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Q2. Difference between persist and cache
Ans. 
Persist stores the data in memory and disk, while cache only stores in memory.
• Persist stores the data both in memory and disk for fault tolerance and recovery.

• Cache only stores the data in memory for faster access.

• Persist is used when the data needs to be recovered in case of failure, while cache is used for temporary storage.

• Example: persist() in Spark RDD saves data to disk, while cache() stores data in memory for fa
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