Free CISI ICWIM Exam Questions

Become CISI Certified with updated ICWIM exam questions and correct answers

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Total 100 Questions | Updated On: Aug 19, 2026

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Question 1

Your organization is using Cloud SQL to manage a production database, and you need to implement a disaster recovery strategy to ensure minimal downtime and data loss in case of a regional failure. What is the best approach to ensure high availability and disaster recovery?

A : Enable automatic backups on a single-zone primary instance.

B : Use a multi-region Cloud Storage bucket for database backups.

C : Set up a primary instance in one region and a read replica in a different region.

D : Configure a primary instance in one zone and a read replica in the same zone.

Answer: C

Question 2

A financial services company needs to implement a data pipeline for transactional data, which must be cleansed and validated for compliance purposes before loading into BigQuery. They also plan to conduct further analytics on the data after loading. Which data manipulation methodology is the most appropriate for these requirements?

A : ETLT (Extract, Transform, Load, Transform) to cleanse data, load it into BigQuery, and conduct additional transformations if needed.

B : ELT (Extract, Load, Transform) to load data into BigQuery and perform data cleaning afterward.

C : Batch SQL imports for compliance validation and transformation after ingestion into BigQuery.

D : ETL (Extract, Transform, Load) to ensure data quality and compliance before loading into BigQuery.

Answer: D

Question 3

You are tasked with designing a data pipeline that ingests daily transaction logs from Cloud Storage, performs transformations to filter and summarize the data, and loads the result into BigQuery. The pipeline needs to be managed and scheduled to run every night at midnight. Which set of Google Cloud products would best meet these requirements?

A : BigQuery ML to perform transformations, Cloud Functions for scheduling, and Cloud Storage as the final destination.

B : Cloud Composer for orchestration, Cloud Dataflow for transformations, and BigQuery as the final storage.

C : Cloud Functions to trigger, Cloud Storage for transformations, and Dataproc as the final destination.

D : Cloud Scheduler to trigger the pipeline, Pub/Sub for transformations, and BigQuery as the final storage.

Answer: B

Question 4

Which two advantages does using pretrained Google Large Language Models (LLMs) via a remote connection in BigQuery offer when working with natural language processing (NLP) tasks? (Select two)

A : Google LLMs enable the immediate use of sophisticated NLP capabilities without requiring model development or training expertise.

B : Google LLMs are primarily suited for numerical data processing, making them less ideal for NLP within BigQuery.

C : BigQuery provides built-in support for custom Python packages, allowing advanced NLP operations on Google LLMs directly.

D : Custom layers can be added to pretrained LLMs directly in BigQuery for domain-specific tuning.

E : Integration with BigQuery ML allows users to query and process large datasets using Google LLMs at scale.

Answer: A,E

Question 5

Your team is running a Dataflow streaming job to process and transform log data in real time. You notice a delay in the processed data reaching BigQuery, which suggests a potential bottleneck in the pipeline. You open the Dataflow Job UI to investigate. Which of the following steps in the Dataflow Job UI would be the most effective first step to identify where the bottleneck is occurring?

A : Enable the Debugging Agent on the Dataflow workers

B : Check the Throughput Metrics for each stage in the Job Graph

C : Adjust the auto-scaling settings in the Dataflow UI

D : View the Execution Details to check the pipeline’s windowing configuration

Answer: B

Page: 1 / 20

Total 100 Questions | Updated On: Aug 19, 2026

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