Capgemini Gcp Data Engineer Interview Questions, Process, and Tips

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

I have experience working on projects involving data processing, transformation, and analysis using GCP services like BigQuery, Dataflow, and Dataproc.

• Utilized BigQuery for storing and querying large datasets

• Implemented data pipelines using Dataflow for real-time data processing

• Utilized Dataproc for running Apache Spark and Hadoop clusters for data processing

• Worked on data ingestion and transformation using Cloud Stora

Window functions in BigQuery are used to perform calculations across a set of table rows related to the current row.

• Window functions allow you to perform calculations on a set of rows related to the current row

• They are used with the OVER() clause in SQL queries

• Common window functions include ROW_NUMBER(), RANK(), and NTILE()

• They can be used to calculate moving averages, cumulative sums, and more

Types of NoSQL databases in GCP include Firestore, Bigtable, and Datastore.

• Firestore is a flexible, scalable database for mobile, web, and server development.

• Bigtable is a high-performance NoSQL database service for large analytical and operational workloads.

• Datastore is a highly scalable NoSQL database for web and mobile applications.

Code to find max number of product by customer

• Iterate through each customer's purchases

• Keep track of the count of each product for each customer

• Find the product with the maximum count for each customer

Creating a dataframe in GCP Data Engineer

• Use the pandas library to create a dataframe

• Provide data in the form of a dictionary or list of lists

• Specify column names if needed