Accenture Lead Data Engineer Interview Questions and Answers

Q1. What are the various data warehousing techniques used, and can you explain them in detail?
Ans. 
Various data warehousing techniques include dimensional modeling, star schema, snowflake schema, and data vault.
• Dimensional modeling involves organizing data into facts and dimensions to facilitate easy querying and analysis.

• Star schema is a type of dimensional modeling where a central fact table is connected to multiple dimension tables.

• Snowflake schema is an extension of star schema where dimension tables are normali...read more
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Q2. How has your analytics work contributed to the organization?
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My analytics work has helped the organization make data-driven decisions, improve operational efficiency, and identify new opportunities for growth.
• Developed data models and algorithms to optimize business processes

• Generated insights from large datasets to drive strategic decision-making

• Identified trends and patterns to improve customer experience and retention

• Implemented data governance policies to ensure data quality
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Q1. How would you respond in various situations?
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I would respond in various situations by remaining calm, assessing the situation, and providing a thoughtful and strategic solution.
• Remain calm and composed

• Assess the situation thoroughly

• Provide a thoughtful and strategic solution

• Communicate effectively with all parties involved
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Q2. What is more important career , team
Ans. 
Both career and team are important, but ultimately career growth should be prioritized.
• Career growth is essential for personal development and achieving professional goals.

• A strong team can support career growth by providing mentorship, collaboration, and opportunities for learning.

• Balancing career and team dynamics is key to long-term success in any role.
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Q1. Questions related to the current and past projects.
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Q2. Aws related questions.
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Q3. Data warehousing basics
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Q1. Explain about the roles and responsibilities.
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Q2. Discussion about the role in Genpact.
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Q1. Asked about expectated salary
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Q2. Why are you switching
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Q1. Asked about data tools other than AWS services
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Q2. When did you use HUDI and Iceberg
Ans. 
I have used HUDI and Iceberg in my previous project for managing large-scale data lakes efficiently.
• Implemented HUDI for incremental data ingestion and managing large datasets in real-time

• Utilized Iceberg for efficient table management and data versioning

• Integrated HUDI and Iceberg with Apache Spark for processing and querying data
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Q1. What is dba, explain the architecture of dba
Ans. 
DBA stands for Database Administrator. The architecture of DBA involves managing and maintaining databases to ensure data integrity and security.
• DBA is responsible for installing, configuring, and upgrading database software.

• They monitor database performance and troubleshoot issues.

• DBA designs and implements backup and recovery strategies to prevent data loss.

• They also manage user access and security permissions within...read more
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Q2. How you will maintain the database and what are the types of backup
Ans. 
Maintaining the database involves regular monitoring, performance tuning, applying patches, and ensuring backups are taken regularly.
• Regularly monitor database performance and usage

• Perform routine maintenance tasks such as applying patches and updates

• Take regular backups to ensure data integrity and disaster recovery

• Implement security measures to protect the database from unauthorized access

• Optimize database performanc
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Q1. Difference between join and lookup
Ans. 
Join is used to combine rows from two or more tables based on a related column, while lookup is used to retrieve data from a reference table based on a matching key.
• Join combines rows from multiple tables based on a related column

• Lookup retrieves data from a reference table based on a matching key

• Join can result in duplicate rows if there are multiple matches, while lookup returns only the first matching row

• Join is use...read more
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Q2. Diffrence between fact table and dimension table
Ans. 
Fact table contains quantitative data and measures, while dimension table contains descriptive attributes.
• Fact table contains numerical data that can be aggregated (e.g. sales revenue, quantity sold)

• Dimension table contains descriptive attributes for analysis (e.g. product name, customer details)

• Fact table is typically normalized, while dimension table is denormalized for faster queries

• Fact table is usually larger in s
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Q3. Sed command to display last before line
Ans. 
Use sed command to display the line before a specific pattern
• Use 'sed -n '/pattern/{g;1!p;};h' file.txt' to display the line before the pattern

• Replace 'pattern' with the specific pattern you are looking for

• This command will display the line before the pattern in the file
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Q1. Data Modeling Concepts, SQL Query
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Q2. Data Governance, Data Lineage, ETL process,
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SQL Scripts to write and also also asked to design an data model of my choice in Telecom Domain

Q1. What is database architecture?
Ans. 
Database architecture refers to the design and structure of a database system.
• Database architecture includes the organization of data, storage, retrieval, and security mechanisms.

• It involves defining the relationships between data elements and how they are stored and accessed.

• Examples of database architectures include hierarchical, network, relational, and object-oriented.

• Database architecture also includes the choice ...read more
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Q2. Difference between delete and truncate
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Delete removes rows one by one, while truncate removes all rows at once.
• Delete is a DML command, while truncate is a DDL command.

• Delete can be rolled back, while truncate cannot be rolled back.

• Delete fires triggers, while truncate does not fire triggers.

• Delete is slower as it logs individual row deletions, while truncate is faster as it logs the deallocation of the data pages.

• Example: DELETE FROM table_name WHERE condi
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Q1. Architecture of sql
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SQL architecture refers to the structure and components of a SQL database system.
• SQL architecture includes components like storage engine, query processor, and buffer manager.

• The storage engine manages data storage and retrieval, while the query processor processes SQL queries.

• The buffer manager handles caching and memory management to optimize performance.

• Examples of SQL architectures include MySQL, Oracle, and SQL Se
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Q2. Recovery models
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