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NEW QUESTION: 1
Which of the following should be disclosed in a summary of significant accounting policies?
I. Management's intention to maintain or vary the dividend payout ratio.
II. Criteria for determining which investments are treated as cash equivalents.
III. Composition of the sales order backlog by segment.
A. I and III.
B. II and III.
C. I only.
D. II only.
Answer: D
Explanation:
Choice "c" is correct. Il only.
The criteria for determining which investments are treated as "cash equivalents" is a method of
accounting policies that needs to be disclosed in the summary of significant accounting policies.
Choice "a" is incorrect. Management's intention to maintain or vary the "dividend payout ratio" is not an
"accounting policy."
Choices "b" and "d" are incorrect. Composition of the sales order backlog by segment is not an
"accounting policy."

NEW QUESTION: 2
Case Study: 7 - Mountkirk Games
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.

Improve uptime - downtime is loss of players.

Increase efficiency of the cloud resources we use.

Reduce latency to all customers.

Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.

Connect to a transactional database service to manage user profiles and game state.

Store game activity in a timeseries database service for future analysis.

As the system scales, ensure that data is not lost due to processing backlogs.

Run hardened Linux distro.

Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity

Process incoming data on the fly directly from the game servers

Process data that arrives late because of slow mobile networks

Allow queries to access at least 10 TB of historical data

Process files that are regularly uploaded by users' mobile devices

Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users.
Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to migrate from their current analytics and statistics reporting model to one that meets their technical requirements on Google Cloud Platform.
Which two steps should be part of their migration plan? (Choose two.)
A. Write a schema migration plan to denormalize data for better performance in BigQuery.
B. Draw an architecture diagram that shows how to move from a single MySQL database to a MySQL cluster.
C. Integrate Cloud Armor to defend against possible SQL injection attacks in analytics files uploaded to Cloud Storage.
D. Evaluate the impact of migrating their current batch ETL code to Cloud Dataflow.
E. Load 10 TB of analytics data from a previous game into a Cloud SQL instance, and run test queries against the full dataset to confirm that they complete successfully.
Answer: A,D

NEW QUESTION: 3
Refer to the code below:

What is displayed when myfunction(true) is called?
A. 2 2 2 2
B. 2 2 1 2
C. 2 2 1 1
D. 2 2 undefined undefined
Answer: C

NEW QUESTION: 4
You plan to deploy Azure IoT Edge devices. Each device will store more than 10,000 images locally. Each image is approximately 5 MB.
You need to ensure that the images persist on the devices for 14 days.
What should you use?
A. Azure Database for Postgres SQL
B. Azure Blob storage on the IoT Edge devices
C. Azure Stream Analytics on the IoT Edge devices
D. Microsoft SQL Server on the IoT Edge devices
Answer: B
Explanation:
Explanation
Azure Blob Storage on IoT Edge provides a block blob and append blob storage solution at the edge. A blob storage module on your IoT Edge device behaves like an Azure blob service, except the blobs are stored locally on your IoT Edge device.
This e is useful where data needs to be stored locally until it can be processed or transferred to the cloud. This data can be videos, images, finance data, hospital data, or any other unstructured data.
References:
https://docs.microsoft.com/en-us/azure/iot-edge/how-to-store-data-blob