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NEW QUESTION: 1
Wofür dienen Capability Maturity Models (CMM) als Benchmark in einer Organisation?
A. Definition von Sicherheitsprofilen
B. Erfahrung in der Branche
C. Prozeduren in der Systementwicklung
D. Personalplanung
Answer: C
NEW QUESTION: 2
A. Option A
B. Option D
C. Option B
D. Option C
Answer: A
Explanation:
CloudWatch is used to monitor AWS as well as the custom services. It provides either basic or detailed
monitoring for the supported AWS products. In basic monitoring, a service sends data points to
CloudWatch every five minutes, while in detailed monitoring a service sends data points to CloudWatch
every minute. The AWS SNS service sends data every 5 minutes. Thus, it supports only the basic
monitoring. The user cannot enable detailed monitoring with SNS.
Reference:
http://docs.aws.amazon.com/AmazonCloudWatch/latest/DeveloperGuide/supported_services.html
NEW QUESTION: 3
How many total processor threads are possible when a customer migrates a workload requiring AIX 5.3 from an 8-core Power 550 to an 8-core Power 750?
A. 0
B. 1
C. 2
D. 3
Answer: A
NEW QUESTION: 4
データマスキング要件を満たすために、各列にどのマスキング関数を実装する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: Default
Default uses a zero value for numeric data types (bigint, bit, decimal, int, money, numeric, smallint, smallmoney, tinyint, float, real).
Only Show a zero value for the values in a column named ShockOilWeight.
Box 2: Credit Card
The Credit Card Masking method exposes the last four digits of the designated fields and adds a constant string as a prefix in the form of a credit card.
Example: XXXX-XXXX-XXXX-1234
Only show the last four digits of the values in a column named SuspensionSprings.
Scenario:
The company identifies the following data masking requirements for the Race Central data that will be stored in SQL Database:
Only Show a zero value for the values in a column named ShockOilWeight.
Only show the last four digits of the values in a column named SuspensionSprings.
Topic 4, ADatum Corporation
Case study
Overview
ADatum Corporation is a retailer that sells products through two sales channels: retail stores and a website.
Existing Environment
ADatum has one database server that has Microsoft SQL Server 2016 installed. The server hosts three mission-critical databases named SALESDB, DOCDB, and REPORTINGDB.
SALESDB collects data from the stored and the website.
DOCDB stored documents that connect to the sales data in SALESDB. The documents are stored in two different JSON formats based on the sales channel.
REPORTINGDB stores reporting data and contains server columnstore indexes. A daily process creates reporting data in REPORTINGDB from the data in SALESDB. The process is implemented as a SQL Server Integration Services (SSIS) package that runs a stored procedure from SALESDB.
Requirements
Planned Changes
ADatum plans to move the current data infrastructure to Azure. The new infrastructure has the following requirements:
* Migrate SALESDB and REPORTINGDB to an Azure SQL database.
* Migrate DOCDB to Azure Cosmos DB.
* The sales data including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytic process will perform aggregations that must be done continuously, without gaps, and without overlapping.
* As they arrive, all the sales documents in JSON format must be transformed into one consistent format.
* Azure Data Factory will replace the SSIS process of copying the data from SALESDB to REPORTINGDB.
Technical Requirements
The new Azure data infrastructure must meet the following technical requirements:
* Data in SALESDB must encrypted by using Transparent Data Encryption (TDE). The encryption must use your own key.
* SALESDB must be restorable to any given minute within the past three weeks.
* Real-time processing must be monitored to ensure that workloads are sized properly based on actual usage patterns.
* Missing indexes must be created automatically for REPORTINGDB.
* Disk IO, CPU, and memory usage must be monitored for SALESDB.
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