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NEW QUESTION: 1
あなたはクエリがこのインデックスを使用しなくても許容できる応答時間内に実行されるかどうかを判断するために見えないように、一意でないインデックスを変更しています。
テーブルの更新は目に見えない索引列に影響を与える実行される場合どの2つが可能ですか。
A. インデックスは表でDMLによって更新されます。
B. インデックスは使用できなくなりますが、テーブルはDMLによって更新されます。
C. インデックスは自動的に表でDMLで更新しているために、目に見えるようになります。
D. インデックスはインデックス付きのテーブル上のDML文では更新されません。
E. インデックスは目に見えないままになります。
Answer: A,E
Explanation:
Unlike unusable indexes, an invisible index is maintained during DML statements.
Note:
*Oracle 11g allows indexes to be marked as invisible. Invisible indexes are maintained like any other index, but they are ignored by the optimizer unless the OPTIMIZER_USE_INVISIBLE_INDEXES parameter is set to TRUE at the instance or session level. Indexes can be created as invisible by using the INVISIBLE keyword, and their visibility can be toggled using the ALTER INDEX command.
NEW QUESTION: 2
You need to send push notifications to policy holders with guaranteed delivery. How would you implement this requirement by using the notifications REST API in MCS?
A. You define the message payload by using the MCS template and utilize the "alert" keyword in the message.. You send individual notifications to APNs, GCM, and WINS, and use the "alert" keyword in the message.
B. You send a unified payload object that addresses the APNs, GCM, and WINS services, and use the "alert" keyword in the message.
C. There is no payload option in MCS that guarantees delivery. You need to find a different way to implement your requirement.
Answer: B
NEW QUESTION: 3
Find the roots, if they exist in the real numbers, of the quadratic equation
A. -4 and 2
B. 1 and 0
C. No real roots
D. 4 and -2
Answer: C
NEW QUESTION: 4
You need to design the unauthorized data usage detection system. What Azure service should you include in the design?
A. Azure Databricks
B. Azure Data Factory
C. Azure Analysis Services
D. Azure SQL Data Warehouse
Answer: D
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 Next 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 Question 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.