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C-C4H630-34 Fragenpool & C-C4H630-34 Prüfungsinformationen - SAP Certified Development Associate - SAP Customer Data Platform PDF Demo - Soaoj

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C-C4H630-34

SAP Certified Development Associate - SAP Customer Data Platform
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NEW QUESTION: 1
다음 중 최고 감사 책임자가 조직의 행동 강령을 준수하기 위해 수행해야 하는 활동은 무엇입니까?
A. 행동 강령의 모든 위반 사항을 검토하고 판결합니다.
B. 강령 감독을 담당하는위원회를 이끌십시오.
C. 규범 위반 사항을 검토하는 위원회의 고문 역할을 합니다.
D. 모든 직원에게 강령을 알리는 절차 시스템을 구현합니다.
Answer: C

NEW QUESTION: 2
로그 정책을 구현해야 합니다.
EventGridController.cs에서 EnsureLogging 메서드를 어떻게 완료해야 합니까? 대답하려면 대답 영역에서 적절한 옵션을 선택하십시오.
참고 : 각각의 올바른 선택은 한 점으로 가치가 있습니다.
C-C4H630-34 Fragenpool
Answer:
Explanation:
C-C4H630-34 Fragenpool
Explanation:
Box 1: logdrop
All log files should be saved to a container named logdrop.
Box 2: 15
Logs must remain in the container for 15 days.
Box 3: UpdateApplicationSettings
All Azure App Service Web Apps must write logs to Azure Blob storage.
References:
https://blog.hompus.nl/2017/05/29/adding-application-logging-blob-to-a-azure-web-app-service-using-powershell/

NEW QUESTION: 3
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
C-C4H630-34 Fragenpool
their loads
Perform analytics on all their orders and shipment logs, which contain both structured and unstructured
C-C4H630-34 Fragenpool
data, to determine how best to deploy resources, which markets to expand 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
C-C4H630-34 Fragenpool
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
C-C4H630-34 Fragenpool
60 virtual machines across 20 physical servers
- Tomcat - Java services
- Nginx - static content
- Batch servers
Storage appliances
C-C4H630-34 Fragenpool
- iSCSI for virtual machine (VM) hosts
- Fibre Channel storage area network (FC SAN) - SQL server storage
- Network-attached storage (NAS) image storage, logs, backups
10 Apache Hadoop /Spark servers
C-C4H630-34 Fragenpool
- Core Data Lake
- Data analysis workloads
20 miscellaneous servers
C-C4H630-34 Fragenpool
- Jenkins, monitoring, bastion hosts,
Business Requirements
Build a reliable and reproducible environment with scaled panty of production.
C-C4H630-34 Fragenpool
Aggregate data in a centralized Data Lake for analysis
C-C4H630-34 Fragenpool
Use historical data to perform predictive analytics on future shipments
C-C4H630-34 Fragenpool
Accurately track every shipment worldwide using proprietary technology
C-C4H630-34 Fragenpool
Improve business agility and speed of innovation through rapid provisioning of new resources
C-C4H630-34 Fragenpool
Analyze and optimize architecture for performance in the cloud
C-C4H630-34 Fragenpool
Migrate fully to the cloud if all other requirements are met
C-C4H630-34 Fragenpool
Technical Requirements
Handle both streaming and batch data
C-C4H630-34 Fragenpool
Migrate existing Hadoop workloads
C-C4H630-34 Fragenpool
Ensure architecture is scalable and elastic to meet the changing demands of the company.
C-C4H630-34 Fragenpool
Use managed services whenever possible
C-C4H630-34 Fragenpool
Encrypt data flight and at rest
C-C4H630-34 Fragenpool
Connect a VPN between the production data center and cloud environment
C-C4H630-34 Fragenpool
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.
Flowlogistic wants to use Google BigQuery as their primary analysis system, but they still have Apache Hadoop and Spark workloads that they cannot move to BigQuery. Flowlogistic does not know how to store the data that is common to both workloads. What should they do?
A. Store the common data in BigQuery and expose authorized views.
B. Store he common data in the HDFS storage for a Google Cloud Dataproc cluster.
C. Store the common data encoded as Avro in Google Cloud Storage.
D. Store the common data in BigQuery as partitioned tables.
Answer: A


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