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NEW QUESTION: 1
If you place walkthrough keyframes close together, camera movement along the path slow down and you can adjust the camera angle to look up and down a fagade.
A. True
B. False
Answer: A

NEW QUESTION: 2
Case Study: 6 - TerramEarth
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About
80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week.
* Support the dealer network with more data on how their customers use their equipment to better
* position new products and services
Have the ability to partner with different companies - especially with seed and fertilizer suppliers
* in the fast-growing agricultural business - to create compelling joint offerings for their customers.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east
* coast.
Create a backup strategy.
* Increase security of data transfer from equipment to the datacenter.
* Improve data in the data warehouse.
* Use customer and equipment data to anticipate customer needs.
* Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2
* - 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs
* - Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server
* - RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?
A. Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzip files to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.
B. Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a MultiRegional Cloud Storage bucket. Upload this data into BigQuery using gcloud. Use Google data Studio for analysis and reporting.
C. Use Cloud Dataproc Hive as the data warehouse. Directly stream data into prtitioned Hive tables.
Use Pig scripts to analyze data.
D. Use BigQuery as the data warehouse. Connect all vehicles to the network and stream data into BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysis and reporting.
Answer: D

NEW QUESTION: 3
You have been tasked with deploying a solution for your company that will store images, which the marketing department will use for its campaigns.
Employees are able to upload images via a web interface, and once uploaded, each image must be resized and watermarked with the company logo.
Image resize and watermark is not time-sensitive and can be completed days after upload if required.
How should you design this solution in the most highly available and cost-effective way?
A. Configure your web application to upload images to the local storage of the web server.
Create a cronjob to execute a script daily that scans this directory for new files and then uses the Amazon EC2 Service API to launch 10 new Amazon EC2 instances, which will resize and watermark the images daily.
B. Configure your web application to upload images to the Amazon Elastic Transcoder service.
Use the Amazon Elastic Transcoder watermark feature to add the company logo as a watermark on your images and then to upload the final images into an Amazon S3 bucket.
C. Configure your web application to upload images to Amazon S3, and send the Amazon S3 bucket URI to an Amazon SQS queue.
Create an Auto Scaling group and configure it to use Spot instances, specifying a price you are willing to pay.
Configure the instances in this Auto Scaling group to poll the SQS queue for new images and then resize and watermark the image before uploading the final images into Amazon S3.
D. Configure your web application to upload images to Amazon S3, and send the S3 object URI to an Amazon SQS queue.
Create an Auto Scaling launch configuration that uses Spot instances, specifying a price you are willing to pay.
Configure the instances in this Auto Scaling group to poll the Amazon SQS queue for new images and then resize and watermark the image before uploading the new images into Amazon S3 and deleting the message from the Amazon SQS queue.
Answer: D