View Cloud Digital Leader Exam Questions

Q: 1

An organization recently launched a virtual customer support agent, generating vast amounts of text and speech data. Why should they use a cloud data warehouse to interpret this data?

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Q: 2

Your organization is moving an application to Google Cloud. As part of that effort, it needs to migrate the application’s working database from another cloud provider to Cloud SQL. The database runs on the MySQL engine. The migration must cause minimal disruption to users. Data must be secured while in transit. Which should your organization use?

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Discussion

Olivia O. Feb 28, 2026 8:14 pm

C . Database Migration Service is built for moving MySQL databases with minimal downtime and encrypts data in transit, which fits the question's requirements. BigQuery DTS isn't for transactional DB migration, and batch insert would cause more disruption. Not 100% if there's edge cases I missed!

Jason Feb 22, 2026 7:27 am

LoganE Feb 18, 2026 12:28 am

Option C

Neha U. Feb 27, 2026 8:13 pm

Option C is the go-to here. Database Migration Service is built for MySQL migrations and supports minimal downtime plus encrypts data in transit. Seen similar advice in official guides, almost always points to DMS for this use case. Anyone see this handled differently?

CalmReviewer9547 Mar 4, 2026 5:43 am

C . Had something like this in a mock, and DMS (option C) was correct for MySQL migrations with tight downtime and secure transit. BigQuery Data Transfer isn’t meant for this kind of DB migration, and batch insert would be disruptive. Not 100% but feels right here.

Ishaan N. Feb 16, 2026 8:29 am

A tbh

Adam E. Mar 4, 2026 5:29 pm

Feels like it could be A. BigQuery Data Transfer Service does handle data moves, just not sure about the minimal disruption part.

AmeliaS Feb 23, 2026 4:01 am

Database Migration Service (C) really fits here since it's designed for MySQL migrations with minimal user impact and secures the connection. Batch insert and BQ transfer can’t meet those downtime or security needs. I'm pretty sure DMS is what Google recommends for this, but open to correction if someone’s done it differently.

MorganP Feb 22, 2026 12:34 pm

Does "minimal disruption" mean zero downtime, or is a short maintenance window acceptable? That could change if Database Migration Service (C) is the clear choice, since it supports continuous replication for near-zero downtime migration.

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Q: 3

Your organization needs to allow a production job to have access to a BigQuery dataset. The production job is running on a Compute Engine instance that is part of an instance group. What should be included in the IAM Policy on the BigQuery dataset?

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Discussion

Aaron L. Feb 25, 2026 4:33 pm

C . The service account is the identity BigQuery checks, not the VM or group. Official practice tests and docs point out this exact thing, so I'd check those again if in doubt.

Daniel H. Feb 25, 2026 8:46 am

Parker Feb 14, 2026 10:43 pm

C . The Compute Engine service account is what BigQuery checks for permissions when the job accesses data. Seen similar stuff on practice tests and that's always the way for least privilege. Project or instance group is too broad here, and D won't cover all cases in a group. Disagree?

Vikram Y. Mar 3, 2026 10:57 pm

C tbh, not D. The instance group is a trap, only the service account actually gets used as the identity for access.

Jordan Feb 14, 2026 3:57 pm

C, not totally sure but service account feels right since it's what BigQuery checks on API requests from Compute Engine.

Robin Feb 16, 2026 8:05 pm

My vote is it's C here. Service account is what actually gets the permissions, not the instance or group. Agree?

Maya E. Feb 24, 2026 12:15 am

I don’t think it’s B or D. The real key is the service account, since that’s what actually does the API call to BigQuery when the job runs. Attaching IAM to the project or instance group would be too broad and not follow least privilege. Bit of a common trap, but C is right from what I know. If someone disagrees, curious to hear their reasoning!

Kevin Feb 28, 2026 1:15 am

C , since the service account is what BigQuery sees when the job runs. Not the project or instance itself. Pretty sure that's the recommended way for least privilege.

Nina P. Feb 14, 2026 4:34 pm

B or D? I always thought attaching IAM at the project level (B) grants downstream access to stuff like BigQuery, but some practice questions push D, saying the instance needs it directly. Not 100% sure-project scope seems more common though. Disagree?

Arjun J. Feb 17, 2026 10:38 am

B tbh, since the project owns the instance and inherits a lot of permissions by default. I always thought project-level roles covered resources in cases like this. Not 100% on it but seems logical, yeah?

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Q: 4

You are currently managing workloads running on Windows Server for which your company owns the licenses. Your workloads are only needed during working hours, which allows you to shut down the instances during the weekend. Your Windows Server licenses are up for renewal in a month, and you want to optimize your license cost. What should you do?

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Q: 5

A Customer has their current SAP systems using Microsoft SQL Server as the Database. They are migrating to Google Cloud and also preparing to later migrate to the latest ver-sion of SAP. The entire IT team is being directed to focus on the migration to the new ver-sion of SAP. The new version of SAP does not use Microsoft SQL Server as the Database, Any but the most critical IT management tasks are being deprioritized, How should they migrate their current database to Google Cloud?

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Discussion

Layla Mar 3, 2026 4:15 am

D imo. It’s managed and supports SQL Server, so less overhead while they prep for the SAP upgrade.

Olivia L. Feb 25, 2026 3:57 am

Probably D, Cloud SQL is managed and handles SQL Server well for migration. Saw similar on official practice test and the guide.

Adam K. Feb 24, 2026 2:13 am

B or maybe A. Bare Metal gives them full control to run SQL Server just like on-prem and could handle any custom SAP configs better than managed services like D. I think that fits since the team might need flexibility even if it's less automated. Not totally sure though, open to other takes.

Piya L. Feb 19, 2026 4:29 am

B looks reasonable to me here since Bare Metal offers direct control and you can run SQL Server just like on-prem. Not as hands-off as D, but if they have custom SAP/SQL configs, I think B might actually fit. Could be wrong though, anyone disagree?

Piya D. Feb 14, 2026 9:05 pm

B or maybe A. Bare Metal gives you more direct control and might be needed for full SQL Server compatibility depending on the SAP setup. I think managed services could be tricky if there's custom tuning, agree?

Logan Feb 20, 2026 3:06 am

B , I saw similar questions in some practice sets. Official guide and exam reviews might help check this.

NoraK Mar 2, 2026 6:27 pm

BigQuery (C) is wrong here since it's not built for running transactional SQL Server workloads. D is the one that supports SQL Server natively and reduces admin effort, which matters because the IT team is focused elsewhere.

Nathan L. Feb 16, 2026 11:32 am

Nah, BigQuery (C) is a trap, it's not the right fit for transactional SQL Server workloads. D makes more sense here given the managed aspect. Pretty sure about that but open to other views.

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Q: 6

Your organization needs to categorize objects in a large group of static images using machine learning. Which Google Cloud product or service should your organization use?

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Q: 7

You are a program manager within a Software as a Service (SaaS) company that offers rendering software for animation studios. Your team needs the ability to allow scenes to be scheduled at will and to be interrupted at any time to restart later. Any individual scene rendering takes less than 12 hours to complete, and there is no service-level agreement (SLA) for the completion time for all scenes. Results will be stored in a global Cloud Storage bucket. The compute resources are not bound to any single geographical location. This software needs to run on Google Cloud in a cost-optimized way. What should you do?

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Q: 8

Your Coustomer's Organization has decided to move to the cloud. They currently run VMs on- promise but their goal on Google cloud is to run containers, primarily on Google Kuber-nete's Engine. They have a lease for their private data center for another year that they have already paid for. What could be strategy they could adopt in migrating?

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Discussion

Chris L. Feb 23, 2026 1:13 pm

B makes the most sense. Since they're not under pressure to move right away, they can refactor the VMs into containers on-prem first and then migrate. Pretty sure "Improve and Move" is about modernizing before moving to GKE, agree?

OliviaN Feb 18, 2026 3:12 pm

Its B

Aaron C. Feb 17, 2026 6:14 pm

Likely B: Had something like this in a mock, and "Improve and Move" is all about using your remaining time on-prem to update VMs into containers before heading to GKE. Since the org already paid for the datacenter, no rush, just modernize locally then shift. Pretty sure that's the idea but open to other takes.

ThoughtfulAuditor7799 Feb 19, 2026 6:56 am

Why do Google always give these cheesy migration names? Realistically, with a year left on the datacenter lease, wouldn't you want to modernize your stuff on-prem first rather than just tossing everything straight into GKE? Or is there some use case where you'd still go for C or D here?

Sam A. Feb 25, 2026 3:28 pm

B tbh

Ajay N. Mar 3, 2026 11:01 am

Makes sense to use B here.

Jordan Feb 23, 2026 7:42 am

Yeah B is the one. Since they've got the datacenter lease covered for another year, they can take their time to modernize VMs to containers on-prem first, then move later. Less pressure and lets them improve before migrating. Pretty sure that's what "Improve and Move" is aiming for here.

Ishaan M. Mar 2, 2026 2:38 pm

Casey Feb 21, 2026 10:31 pm

Probably D, not B.

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Q: 9

Your organization wants to be sure that is expenditures on cloud services are in line with the budget. Which two Google Cloud cost management features help your organization gain greater visibility into its cloud resource costs? (Choose two.)

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Discussion

Casey B. Feb 25, 2026 4:31 am

B and D, if the question meant enforcing budget rules instead of just visibility.

QuickLearner2121 Feb 22, 2026 4:06 am

B A and B are the best picks here. Billing dashboards show actual spend and resource labels let you break down costs by team or project. D is tempting but more about policy than visibility, right? Pretty sure these are what Google expects.

Reese L. Feb 27, 2026 4:17 am

Its A and B here. Billing dashboards show you spend totals and trends, and resource labels let you break costs out by team or project for more granular tracking. D is tempting but it's focused on enforcing policies, not visualizing spend. Think the main trap was D-anyone disagree?

Piya O. Mar 2, 2026 7:32 am

A and B

Meera S. Feb 20, 2026 9:53 pm

Maybe D , would pick D over B since policies can also help show compliance. Possible trap with labels though.

Jordan C. Feb 19, 2026 11:58 am

A and B make sense to me for visibility. Billing dashboards let you see overall cloud spending, while resource labels break things down by project or team. D is more about policy than showing actual usage. Pretty sure these are the main tools for cost transparency here. Anyone see another angle?

HelpfulArchitect1158 Feb 26, 2026 5:45 am

D A and B nail it for visibility. C is a trap since discounts help reduce costs, not track them. If someone sees value in D for visibility, let me know but I think it's mainly about policy.

Mason Feb 18, 2026 11:37 am

Option A and B for me too. Labels and billing dashboards both let you actually see what’s being spent and where. Haven’t seen D used for pure visibility, so I’d stick with AB unless someone’s got other info.

Sara F. Mar 5, 2026 4:47 pm

D imo A and B fit best here. Billing dashboards (A) give you a real-time overview of where your spend is going, so you can spot overages or unexpected charges quickly. Resource labels (B) let you tag resources to break down costs by project or team in reports-super useful for tracking. Not 100% sure though if there's a tricky option hiding, but A and B match what I've seen in similar practice sets.

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Q: 10

Your organization wants to predict the behavior of visitors to its public website. To do that, you have decided to build a machine learning model. Your team has database-related skills but only basic machine learning skills, and would like to use those database skills. Which Google Cloud product or feature should your organization choose?

Options

Discussion

Amelia W. Mar 2, 2026 3:12 am

Option A Saw a similar question in practice sets, pretty sure BigQuery ML lets you run ML models using SQL so database folks can stick to what they know.

Logan B. Feb 18, 2026 6:41 am

Feels like D since Cloud SQL matches their database experience and keeps everything familiar. Still, not totally sure if it covers ML part.

Parker V. Feb 19, 2026 2:37 pm

D imo. Since their team already knows databases, Cloud SQL seems like the easiest path. I think you could leverage familiar SQL tools that way, unless the question is expecting more actual ML features.

SeasonedLearner9005 Feb 16, 2026 12:18 am

C or D for me. Since the team only has basic ML skills, I was thinking Cloud SQL (D) might be the right fit because it's database-oriented and familiar to them. But reading closely, just having a database doesn't help with ML modeling directly, so maybe C (TensorFlow) is better if they want to actually build models. Not totally confident though-anyone see it differently?

PracticalSec6597 Feb 28, 2026 9:39 am

Its D, since Cloud SQL uses standard SQL for queries and should fit a database team's skills.

Chris Y. Feb 22, 2026 10:42 pm

Don't think it's C. While TensorFlow is powerful for ML, it's not really aimed at folks with just SQL skills. D seems tempting because of the database angle, but it doesn't help you build ML models directly.

Karan G. Feb 27, 2026 9:16 am

Feels like A. Database teams can use SQL with BigQuery ML for building models, so fits better than Cloud SQL or the others.

Amelia G. Feb 27, 2026 11:44 am

I don't think it's D. Cloud SQL is just a managed database, doesn't actually let you build ML models within SQL itself. BigQuery ML seems like a trap here, but I get why folks mix them up since both involve SQL skills. Anyone else see it different?

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