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NEW QUESTION: 1
Universal Containersのマーケティング部門は、従来のキャンペーンとメール管理システムからSalesforceに移行しており、コミュニケーション資料も確実に移行できるようにしたいと考えています。マーケティング部門のメールテンプレートを移行するためにコンサルタントは何をすすめるべきですか？
A. メールテンプレートをSalesforceに送信する前に、メールto Salesforceを有効にします。
B. Salesforceでメールおよび差し込み印刷テンプレートを手動で再作成します。
C. メールテンプレートの変更セットを作成するか、照明プラットフォームを使用します。
D. 閉じるためのメールを有効にして、インポートウィザードを使用します。
Answer: B

NEW QUESTION: 2
DRAG DROP
You have a table named HumanResources.Employee. You configure the table to use a default history table that contains 10 years of data.
You need to write a query that retrieves the values of the BusinessEntityID and JobTitle fields. You must retrieve all historical data up to January 1, 2017 where the value of the BusinessEntityID column equals 4.
Which four Transact-SQL segments should you use to develop the solution? To answer, move the appropriate Transact-SQL segments to the answer area and arrange them in the correct order.

Answer:
Explanation:

Explanation:

References: https://docs.microsoft.com/en-us/sql/relational-databases/tables/querying-data-in-a-system-versioned-temporal-table

NEW QUESTION: 3
You need to design the unauthorized data usage detection system. What Azure service should you include in the design?
A. Azure SQL Data Warehouse
B. Azure Data Factory
C. Azure Databricks
D. Azure Analysis Services
Answer: A
Explanation:
Explanation
SQL Database and SQL Data Warehouse
SQL threat detection identifies anomalous activities indicating unusual and potentially harmful attempts to access or exploit databases.
Advanced Threat Protection for Azure SQL Database and SQL Data Warehouse detects anomalous activities indicating unusual and potentially harmful attempts to access or exploit databases.
Scenario:
Requirements. Security
The solution must meet the following security requirements:
Unauthorized usage of data must be detected in real time. Unauthorized usage is determined by looking for unusual usage patterns.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-threat-detection-overview
Topic 6, Litware Case
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the button to return to the question.
Overview
Litware, Inc. owns and operates 300 convenience stores across the US. The company sells a variety of packaged foods and drinks, as well as a variety of prepared foods, such as sandwiches and pizzas.
Litware has a loyalty club whereby members can get daily discounts on specific items by providing their membership number at checkout.
Litware employs business analysts who prefer to analyze data by using Microsoft Power BI, and data scientists who prefer analyzing data in Azure Databricks notebooks.
Requirements. Business Goals
Litware wants to create a new analytics environment in Azure to meet the following requirements:
* See inventory levels across the stores. Data must be updated as close to real time as possible.
* Execute ad hoc analytical queries on historical data to identify whether the loyalty club discounts increase sales of the discounted products.
* Every four hours, notify store employees about how many prepared food items to produce based on historical demand from the sales data.
Requirements. Technical Requirements
Litware identifies the following technical requirements:
* Minimize the number of different Azure services needed to achieve the business goals
* Use platform as a service (PaaS) offerings whenever possible and avoid having to provision virtual machines that must be managed by Litware.
* Ensure that the analytical data store is accessible only to the company's on-premises network and Azure services.
* Use Azure Active Directory (Azure AD) authentication whenever possible.
* Use the principle of least privilege when designing security.
* Stage inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use.
Files that have a modified date that is older than 14 days must be removed.
* Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
* Ensure that you can quickly restore a copy of the analytical data store within one hour in the event of corruption or accidental deletion.
Requirements. Planned Environment
Litware plans to implement the following environment:
* The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure.
* Customer data, including name, contact information, and loyalty number, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Product data, including product ID, name, and category, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Daily inventory data comes from a Microsoft SQL server located on a private network.
* Litware currently has 5 TB of historical sales data and 100 GB of customer data. The company expects approximately 100 GB of new data per month for the next year.
* Litware will build a custom application named FoodPrep to provide store employees with the calculation results of how many prepared food items to produce every four hours.
* Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure.