Accenture Gcp Data Engineer Interview Questions, Process, and Tips

The GCP services used in our project include BigQuery, Dataflow, Pub/Sub, and Cloud Storage.

• BigQuery for data warehousing and analytics

• Dataflow for real-time data processing

• Pub/Sub for messaging and event ingestion

• Cloud Storage for storing data and files

Cloud Functions are event-driven functions that run in response to cloud events.

• Serverless functions that automatically scale based on demand

• Can be triggered by events from various cloud services

• Supports multiple programming languages like Node.js, Python, etc.

To schedule a job to trigger every hour in Airflow, you can use the Cron schedule interval

• Define a DAG (Directed Acyclic Graph) in Airflow

• Set the schedule_interval parameter to '0 * * * *' to trigger the job every hour

• Example: schedule_interval='0 * * * *'

Use Python's slicing feature to display a string in reverse order.

• Use string slicing with a step of -1 to reverse the string.

• Example: 'hello'[::-1] will output 'olleh'.

Pub/Sub is a messaging service that allows communication between independent applications.

• Pub/Sub is used for real-time messaging and event-driven systems.

• It is commonly used for data ingestion, streaming analytics, and event-driven architectures.

• Examples of Pub/Sub services include Google Cloud Pub/Sub, Apache Kafka, and Amazon SNS/SQS.

Google Cloud BigQuery is a fully-managed, serverless data warehouse that uses a distributed architecture for processing and analyzing large datasets.

• BigQuery uses a distributed storage system called Capacitor for storing and managing data.

• It uses a distributed query engine called Dremel for executing SQL-like queries on large datasets.

• BigQuery separates storage and compute, allowing users to scale compute resources ind...read more

List and tuple are both used to store collections of data, but they have some differences.

• Lists are mutable while tuples are immutable

• Lists use square brackets [] while tuples use parentheses ()

• Lists are typically used for collections of homogeneous data while tuples are used for heterogeneous data

• Lists have more built-in methods than tuples

Developed a data pipeline to ingest, process, and analyze customer feedback data for a retail company.

• Used Google Cloud Platform services like BigQuery, Dataflow, and Pub/Sub for data processing.

• Implemented data cleansing and transformation techniques to ensure data quality.

• Created visualizations and dashboards using tools like Data Studio for stakeholders to easily interpret the data.

GCP offers different storage classes for varying performance and cost requirements.

• Standard Storage: for frequently accessed data

• Nearline Storage: for data accessed less frequently

• Coldline Storage: for data accessed very infrequently

• Archive Storage: for data stored for long-term retention

SQL optimization techniques focus on improving query performance by reducing execution time and resource usage.

• Use indexes to speed up data retrieval

• Avoid using SELECT * and instead specify only the columns needed

• Optimize joins by using appropriate join types and conditions

• Limit the use of subqueries and instead use JOINs where possible

• Use EXPLAIN to analyze query execution plans and identify bottlenecks

BigQuery is used for analyzing large datasets and running complex queries, while SQL is used for querying databases.

• BigQuery is used for analyzing large datasets quickly and efficiently

• SQL is used for querying databases to retrieve specific data

• BigQuery can handle petabytes of data, making it ideal for big data analysis

• SQL can be used to perform operations like filtering, sorting, and aggregating data