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Career Opportunities

The certified individuals can explore a variety of job opportunities. Some of the positions that they can take up include a Software Engineer, a Cloud Architect, a Data Engineer, a Sales Engineer, a Data Scientist, a Cloud Developer, and a Kubernetes Architect, among others. The salary outlook for these job roles is an average of $128,500 per annum.

To become a Google Certified Professional Data Engineer, a candidate must pass the certification exam, which costs $200. Professional-Data-Engineer exam is available in English, Japanese, and Spanish and can be taken online or at a testing center. Professional-Data-Engineer Exam is valid for two years, after which a candidate must recertify to maintain their certification.

Google Professional-Data-Engineer certification is a highly respected and sought-after credential in the field of data engineering. Google Certified Professional Data Engineer Exam certification is offered by Google Cloud and is designed for professionals who are skilled in designing and building data processing systems on the Google Cloud Platform. Professional-Data-Engineer exam tests candidates' knowledge of data engineering principles, including data collection, transformation, storage, and analysis.

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Google Certified Professional Data Engineer Exam Sample Questions (Q63-Q68):

NEW QUESTION # 63
You need (o give new website users a globally unique identifier (GUID) using a service that takes in data points and returns a GUID This data is sourced from both internal and external systems via HTTP calls that you will make via microservices within your pipeline There will be tens of thousands of messages per second and that can be multithreaded, and you worry about the backpressure on the system How should you design your pipeline to minimize that backpressure?

Answer: D


NEW QUESTION # 64
You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?

Answer: B


NEW QUESTION # 65
You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

Answer: C


NEW QUESTION # 66
Which of these is NOT a way to customize the software on Dataproc cluster instances?

Answer: D

Explanation:
Explanation
You can access the master node of the cluster by clicking the SSH button next to it in the Cloud Console.
You can easily use the --properties option of the dataproc command in the Google Cloud SDK to modify many common configuration files when creating a cluster.
When creating a Cloud Dataproc cluster, you can specify initialization actions in executables and/or scripts that Cloud Dataproc will run on all nodes in your Cloud Dataproc cluster immediately after the cluster is set up. [https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/init-actions] Reference: https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/cluster-properties


NEW QUESTION # 67
Case Study 1 - Flowlogistic
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 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
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
* 10 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.
Flowlogistic's management has determined that the current Apache Kafka servers cannot handle the data volume for their real-time inventory tracking system. You need to build a new system on Google Cloud Platform (GCP) that will feed the proprietary tracking software. The system must be able to ingest data from a variety of global sources, process and query in real-time, and store the data reliably. Which combination of GCP products should you choose?

Answer: B

Explanation:
Pub/Sub -> Dataflow for real time processing requirements.
https://codelabs.developers.google.com/codelabs/cpb104-pubsub/#0


NEW QUESTION # 68
......

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