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NEW QUESTION: 1
An enterprise company's data science team wants to provide a safe, cost-effective way to provide easy access to Amazon SageMaker. The data scientists have limited AWS knowledge and need to be able to launch a Jupyter notebook instance. The notebook instance needs to have a preconfigured AWS KMS key to encrypt data at rest on the machine learning storage volume without exposing the complex setup requirements.
Which approach will allow the company to set up a self-service mechanism for the data scientists to launch Jupyter notebooks in its AWS accounts with the LEAST amount of operational overhead?
A. Create a serverless front end using a static Amazon S3 website to allow the data scientists to request a Jupyter notebook instance by filling out a form. Use Amazon API Gateway to receive requests from the S3 website and trigger a central AWS Lambda function to make an API call to Amazon SageMaker that launch a notebook instance with a preconfigured KMS key for the data scientists. Then call back to the front-end website to display the URL to the notebook instance.
B. Create an AWS CloudFormation template to launch a Jupyter notebook instance using the AWS::SageMaker::Notebooklnstance resource type with a preconfigured KMS key. Simplify the parameter names, such as the instance size, by mapping them to Small, Large, and X-Large using the Mappings section in CloudFormation. Display the URL to the notebook using the Outputs section, then upload the template into an AWS Service Catalog product in the data scientist's portfolio, and share it with the data scientist's IAM role.
C. Create an AWS CloudFormation template to launch a Jupyter notebook instance using the AWS::SaqeMaker::Notebooklnstance resource type with a preconfigured KMS key. Add a user-friendly name to the CloudFormation template. Display the URL to the notebook using the Outputs section. Distribute the CloudFormation template to the data scientists using a shared Amazon S3 bucket.
D. Create an AWS CLI script that the data scientists can run locally. Provide step-by-step instructions about the parameters to be provided while executing the AWS CLI script to launch a Jupyter notebook with a preconfigured KMS key. Distribute the CLI script to the data scientists using a shared Amazon S3 bucket.
Answer: B
Explanation:
https://aws.amazon.com/blogs/mt/enable-self-service-secured-data-science-using-amazon-sagemaker-notebooks-and-aws-service-catalog/

NEW QUESTION: 2
Hinweis: Diese Frage ist Teil einer Reihe von Fragen, die dasselbe Szenario verwenden. Zur Vereinfachung wird das Szenario in jeder Frage wiederholt. Jede Frage stellt ein anderes Ziel und eine andere Antwortauswahl dar, aber der Text des Szenarios ist in jeder Frage dieser Reihe genau gleich.
Sie haben eine Datenbank mit dem Namen Sales, die die folgenden Datenbanktabellen enthält: Customer, Order und Products.
Die Tabelle "Produkte" und die Tabelle "Bestellung" sind in der folgenden Abbildung dargestellt.

Die Kundentabelle enthält eine Spalte, in der die Daten für die letzte Bestellung des Kunden gespeichert sind.
Sie planen, eine Tabelle mit dem Namen Leads zu erstellen. Es wird erwartet, dass die Tabelle Leads ungefähr 20.000 Datensätze enthält.
Der Speicherbedarf für die Leads-Tabelle muss minimiert werden.
Sie müssen das Datenbankdesign ändern, um die folgenden Anforderungen zu erfüllen:
* Zeilen in der Orders-Tabelle müssen immer einen gültigen Wert für die ProductID-Spalte haben.
* Zeilen in der Tabelle "Produkte" dürfen nicht gelöscht werden, wenn sie Teil von Zeilen in der Tabelle "Bestellungen" sind.
* Alle Zeilen in beiden Tabellen müssen eindeutig sein.
Identifizieren Sie in der folgenden Tabelle die Einschränkung, die für jede Tabelle konfiguriert werden muss.
HINWEIS: Nehmen Sie in jeder Spalte nur eine Auswahl vor.

Answer:
Explanation:

Explanation

A FOREIGN KEY in one table points to a PRIMARY KEY in another table. Here the foreign key constraint is put on the ProductID in the Orders, and points to the ProductID of the Products table.
With a check constraint on the ProductID we can ensure that the Products table contains only unique rows.
References:
http://www.w3schools.com/sql/sql_foreignkey.asp

NEW QUESTION: 3
As a Line Manager within the organization you are able to do a search on restricted worker information within the Directory.
What values are you able to search on that workers and HR Administrators are not able to?
A. Worker Competencies, languages, licenses and certifications, and school education information within the Talent Profile.
B. Worker Competencies, work location, department, and languages.
C. Work location, department, job title, and school education.
D. Worker Competencies. Areas of Expertise. Areas of Interest, and school education.
Answer: B