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NEW QUESTION: 1
GTM solves which three of these standard DNS limitations?
A. It can verify that a client does not have any viruses before sending the IP address
B. It can verify that a host is available before resolving a host name for a client
C. It has more complex load balancing methods
D. It can use HTTPS for the connection between itself and the client
E. It can ensure that clients remain at the same data center for stateful applications
Answer: B,C,E
Explanation:
Explanation/Reference:
Explanation:
GTM solves three of these standard DNS limitations
It can verify that ahost is available before resolving a host name for a client It can ensure that clients remain at the same data center for stateful applications It has more complex load balancing methods

NEW QUESTION: 2
구매 요구 사항을 구현해야 합니다.
당신은 무엇을 해야 합니까?
A. Bot FrameworkREST API 첨부 작업을 사용하여 사용자의 음성을 보내고 Speech Service API는 인 텐트를 인식합니다.
B. Bot Framework REST API 대화 작업을 사용하여 사용자의 음성을 보내고 Speech Service API는 인 텐트를 인식합니다.
C. 직접 REST API를 사용하여 사용자의 음성을 보내고 Speech Service API를 사용하여 인 텐트를 인식합니다.
D. Speech Service API를 사용하여 사용자의 음성과 Bot Framework REST API 대화 작업을 보내어 인 텐트를 인식합니다.
Answer: B
Explanation:
Scenario: Enable users to place an order for delivery or pickup by using their voice.
You must develop a chatbot by using the Bot Builder SDK and Language Understanding Intelligence Service (LUIS). The chatbot must allow users to order food for pickup or delivery.
The Bot Framework REST APIs enable you to build bots that exchange messages with channels configured in the Bot Framework Portal, store and retrieve state data, and connect your own client applications to your bots. All Bot Framework services use industry-standard REST and JSON over HTTPS.
The Speech Service API is used to recognize intents.
References:
https://docs.microsoft.com/en-us/azure/bot-service/rest-api/bot-framework-rest-connector-concepts?view=azure-bot-service-4.0
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-recognize-intents-from-speech-cpp

NEW QUESTION: 3
Examine the parameters for your database instance:
NAMETYPEVALUE
optimizer_adaptive_reporting_onlybooleanFALSE
optimizer_capture_sql_plan_baselinesbooleanFALSE
optimizer_dynamic_samplinginteger2
optimizer_features_enablestring12.1.0.1
Which three statements are true about the process of automatic optimization by using statistics feedback?
A. The optimizer does not monitor cardinality feedback if dynamic sampling and multicolumn statistics are enabled.
B. After the optimizer identifies a query as a re-optimization candidate, statistics collected by the collectors are submitted to the optimizer.
C. The optimizer enables monitoring for cardinality feedback after the first execution of a query.
D. The optimizer can re optimize a query only once using cardinality feedback.
E. The optimizer automatically changes a plan during subsequent execution of a SQL statement if there is a huge difference in optimizer estimates and execution statistics.
Answer: A,C,E
Explanation:
C: During the first execution of a SQL statement, an execution plan is generated as usual.
D: if multi-column statistics are not present for the relevant combination of columns, the optimizer can fall back on cardinality feedback.
(not B)* Cardinality feedback. This feature, enabled by default in 11.2, is intended to improve plans for repeated executions.
optimizer_dynamic_sampling optimizer_features_enable
Dynamic sampling or multi-column statistics allow the optimizer to more accurately estimate selectivity of conjunctive predicates.
Note:
* OPTIMIZER_DYNAMIC_SAMPLING controls the level of dynamic sampling performed by the optimizer. Range of values. 0 to 10
Cardinality feedback was introduced in Oracle Database 11gR2. The purpose of this feature is to automatically improve plans for queries that are executed repeatedly, for which the optimizer does not estimate cardinalities in the plan properly. The optimizer may misestimate cardinalities for a variety of reasons, such as missing or inaccurate statistics, or complex predicates. Whatever the reason for the misestimate, cardinality feedback may be able to help.

NEW QUESTION: 4
Hintergrund
Sie verwalten eine Umgebung mit mehreren Mandanten, die in Microsoft Azure gehostet wird. Alle Änderungen an der Datenbank werden in eine Vorlagendatenbank übertragen, die als Microsoft Azure SQL-Datenbank mit dem Namen contosoTempiate gespeichert ist und auf dem virtuellen SQL Server mit dem Namen SQL1 gespeichert ist. Sie haben auch einen virtuellen SQL Server namens SQL2.
Sie stellen eine Azure SQL-Datenbankinstanz mit dem Namen DB1 bereit. Es wurden keine Azure-Firewallregeln erstellt.
Sie planen, die folgenden Datenbanken in einem elastischen Pool bereitzustellen: EDB2, EDB3, EDB4, EDB5 und EDB6. Alle Datenbanken im Pool weisen dieselbe Spitzenverwendungsdauer auf.
Sie migrieren eine SQL Server-Instanz mit dem Namen srvi auf eine virtuelle Maschine der Azure DS-13-Serie. Die VM verfügt über zwei Premium-Festplatten, die als Speicherpool zugeordnet sind.
Sie planen, eine neue Azure SQL-Datenbank mit dem Namen DB7 bereitzustellen, um eine Anwendung für Ihre Personalabteilung zu unterstützen.
Sie sollten verhindern, dass Benutzer, die keine Administratoren sind, vertrauliche Daten anzeigen, die in DB7 gespeichert sind. Sie sollten dies tun, ohne Codeänderungen an den verschiedenen Anwendungen vorzunehmen, die die Daten lesen.
Unternehmensziele für die Datenmaskierung erfordern die folgenden Formate:

Sie müssen für jeden Feldtyp eine dynamische Datenmaskierung implementieren.
Wie soll die Transact-SQL-Anweisung ausgefüllt werden? Ziehen Sie zum Beantworten die entsprechenden Transact-SQL-Segmente an die richtigen Positionen. Jedes Transact-SQL-Segment kann einmal, mehrmals oder gar nicht verwendet werden. Möglicherweise müssen Sie die geteilte Leiste zwischen den Fenstern ziehen oder einen Bildlauf durchführen, um den Inhalt anzuzeigen.

Answer:
Explanation:

Explanation

Box 1: ADD MASKED WITH(FUNCTION = 'email()')
The email masking method exposes the first letter of an email address and the constant suffix ".com", in the form of an email address. . [email protected].
This default behavior is what we want.
Example definition syntax: Email varchar(100) MASKED WITH (FUNCTION = 'email()') NULL Box 2: ADD MASKED WITH(FUNCTION = 'partial(2,"XX-XX-XX",2) The custom masking method which exposes the first and last letters and adds a custom padding string in the middle. Syntax: prefix,[padding],suffix References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking?view=sql-server-2017