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このラインで優秀なエリートになりたい場合は、Professional-Data-Engineer認定を取得する必要があります。したがって、資格試験の重要性を通してそれを確認できます。資格試験を通じてのみ、対応する資格証明書を取得しているため、関連作業に従事することができます。そのため、Professional-Data-Engineerテストの急流は、比較的短期間で人々が資格試験に合格するための非常に重要なツールです。 Professional-Data-Engineer学習ツールを選択すると、ユーザーが困難な点をすばやく分析し、Professional-Data-Engineer試験に合格するのに役立ちます。
| Section | Weight | Objectives |
|---|---|---|
| Building and operationalizing data processing systems | 24% | - Data processing and transformation
|
| Operationalizing machine learning models | 26% | - Model deployment and monitoring
|
| Ensuring solution quality | 28% | - Security and governance
|
| Designing data processing systems | 22% | - Data architecture and storage design
|
>> Professional-Data-Engineer問題例 <<
当社は長年にわたり、クライアントに最高のProfessional-Data-Engineer練習問題を提供し、テストProfessional-Data-Engineer認定試験にスムーズに合格できるように常に努めています。当社は、国内の有名な業界の専門家を募集し、優秀な人材をProfessional-Data-Engineer学習ガイドを編集し、お客様に心から奉仕するために最善を尽くしました。当社は、お客様が私たちの神であり、Professional-Data-Engineerトレーニング資料の品質に関する厳格な基準であるというサービス理念を設定しています。
質問 # 393
You work for a large ecommerce company. You are using Pub/Sub to ingest the clickstream data to Google Cloud for analytics. You observe that when a new subscriber connects to an existing topic to analyze data, they are unable to subscribe to older data for an upcoming yearly sale event in two months, you need a solution that, once implemented, will enable any new subscriber to read the last 30 days of dat a. What should you do?
正解：D
解説：
By setting the topic retention policy to 30 days, you can ensure that any new subscriber can access the messages that were published to the topic within the last 30 days1. This feature allows you to replay previously acknowledged messages or initialize new subscribers with historical data2. You can configure the topic retention policy by using the Cloud Console, the gcloud command-line tool, or the Pub/Sub API1.
Option A is not efficient, as it requires creating a new topic and duplicating the data for each new subscriber, which would increase the storage costs and complexity. Option C is not effective, as it only affects the unacknowledged messages in a subscription, and does not allow new subscribers to access older data3. Option D is not feasible, as it depends on the source system's ability and willingness to re-push the data, and it may cause data duplication or inconsistency. Reference:
1: Create a topic | Cloud Pub/Sub Documentation | Google Cloud
2: Replay and purge messages with seek | Cloud Pub/Sub Documentation | Google Cloud
3: When is a PubSub Subscription considered to be inactive?
質問 # 394
Which of the following is not true about Dataflow pipelines?
正解：A
解説：
The data and transforms in a pipeline are unique to, and owned by, that pipeline. While your program can create multiple pipelines, pipelines cannot share data or transforms Reference: https://cloud.google.com/dataflow/model/pipelines
質問 # 395
Your software uses a simple JSON format for all messages. These messages are published to Google Cloud Pub/Sub, then processed with Google Cloud Dataflow to create a real-time dashboard for the CFO. During testing, you notice that some messages are missing in thedashboard. You check the logs, and all messages are being published to Cloud Pub/Sub successfully. What should you do next?
正解：D
解説：
Topic 1, Flowlogistic Case Study
Company Overview
Flowlogistic is a leading logistics and supply chain provider. They help businesses throughout the world manage their resources and transport them to their final destination. The company has grown rapidly, expanding their offerings to include rail, truck, aircraft, and oceanic shipping.
Company Background
The company started as a regional trucking company, and then expanded into other logistics market. Because they have not updated their infrastructure, managing and tracking orders and shipments has become a bottleneck. To improve operations, Flowlogistic developed proprietary technology for tracking shipments in real time at the parcel level. However, they are unable to deploy it because their technology stack, based on Apache Kafka, cannot support the processing volume. In addition, Flowlogistic wants to further analyze their orders and shipments to determine how best to deploy their resources.
Solution Concept
Flowlogistic wants to implement two concepts using the cloud:
* Use their proprietary technology in a real-time inventory-tracking system that indicates the location of their loads
* Perform analytics on all their orders and shipment logs, which contain both structured and unstructured data, to determine how best to deploy resources, which markets toexpand info. They also want to use predictive analytics to learn earlier when a shipment will be delayed.
Existing Technical Environment
Flowlogistic architecture resides in a single data center:
* Databases
* 8 physical servers in 2 clusters
* SQL Server - user data, inventory, static data
* 3 physical servers
* Cassandra - metadata, tracking messages
10 Kafka servers - tracking message aggregation and batch insert
* Application servers - customer front end, middleware for order/customs
* 60 virtual machines across 20 physical servers
* Tomcat - Java services
* Nginx - static content
* Batch servers
Storage appliances
* iSCSI for virtual machine (VM) hosts
* Fibre Channel storage area network (FC SAN) - SQL server storage
* Network-attached storage (NAS) image storage, logs, backups
* Apache Hadoop /Spark servers
* Core Data Lake
* Data analysis workloads
* 20 miscellaneous servers
* Jenkins, monitoring, bastion hosts,
Business Requirements
* Build a reliable and reproducible environment with scaled panty of production.
* Aggregate data in a centralized Data Lake for analysis
* Use historical data to perform predictive analytics on future shipments
* Accurately track every shipment worldwide using proprietary technology
* Improve business agility and speed of innovation through rapid provisioning of new resources
* Analyze and optimize architecture for performance in the cloud
* Migrate fully to the cloud if all other requirements are met
Technical Requirements
* Handle both streaming and batch data
* Migrate existing Hadoop workloads
* Ensure architecture is scalable and elastic to meet the changing demands of the company.
* Use managed services whenever possible
* Encrypt data flight and at rest
* Connect a VPN between the production data center and cloud environment SEO Statement We have grown so quickly that our inability to upgrade our infrastructure is really hampering further growth and efficiency. We are efficient at moving shipments around the world, but we are inefficient at moving data around.
We need to organize our information so we can more easily understand where our customers are and what they are shipping.
CTO Statement
IT has never been a priority for us, so as our data has grown, we have not invested enough in our technology.
I have a good staff to manage IT, but they are so busy managing our infrastructure that I cannot get them to do the things that really matter, such as organizing our data, building the analytics, and figuring out how to implement the CFO' s tracking technology.
CFO Statement
Part of our competitive advantage is that we penalize ourselves for late shipments and deliveries. Knowing where out shipments are at all times has a direct correlation to our bottom line and profitability. Additionally, I don't want to commit capital to building out a server environment.
質問 # 396
You want to build a managed Hadoop system as your data lake. The data transformation process is composed of a series of Hadoop jobs executed in sequence. To accomplish the design of separating storage from compute, you decided to use the Cloud Storage connector to store all input data, output data, and intermediary data. However, you noticed that one Hadoop job runs very slowly with Cloud Dataproc, when compared with the on-premises bare-metal Hadoop environment (8-core nodes with 100-GB RAM). Analysis shows that this particular Hadoop job is disk I/O intensive. You want to resolve the issue. What should you do?
正解：C
解説：
Its google recommended approach to use LocalDisk/HDFS to store Intermediate result and use Cloud Storage for initial and final results.
質問 # 397
Your financial services company is moving to cloud technology and wants to store 50 TB of financial time- series data in the cloud. This data is updated frequently and new data will be streaming in all the time. Your company also wants to move their existing Apache Hadoop jobs to the cloud to get insights into this data. Which product should they use to store the data?
正解：B
解説：
https://cloud.google.com/blog/products/databases/getting-started-with-time-series-trend-predictions-using-gcp
質問 # 398
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IT認証試験に合格したい受験生の皆さんはきっと試験の準備をするために大変悩んでいるでしょう。しかし準備しなければならないのですから、落ち着かない心理になりました。しかし、JPNTestのGoogleのProfessional-Data-Engineerトレーニング資料を利用してから、その落ち着かない心はなくなった人がたくさんいます。JPNTestのGoogleのProfessional-Data-Engineerトレーニング資料を持っていたら、自信を持つようになります。試験に合格しない心配する必要がないですから、気楽に試験を受けることができます。これは心のヘルプだけではなく、試験に合格することで、明るい明日を持つこともできるようになります。
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