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NEW QUESTION: 1
You are configuring the Certification Authority role service. From the Certification Authority console, you enable logging. You need to ensure that configuration changes to the certification authority (CA) are logged.
Which audit policy should you configure?
A. Audit privilege use
B. Audit policy change
C. Audit object access
D. Audit system events
Answer: C
Explanation:
Explanation/Reference:
Explanation:
ADatum identifies the following security requirements:
An offline root certification authority (CA) must be configured.

Client computers must be issued certificates by a server in their local office.

Changes to the CA configuration settings and the CA security settings must be logged.

Client computers must be able to renew certificates automatically over the Internet.

The number of permissions and privileges assigned to users must be minimized whenever possible.

Users from a group named Group1 must be able to create new instances of App1 in the private cloud.

Client computers must be issued new certificates when the computers are connected to the local

network only.
The virtual machines used to host App2 must use BitLocker Drive Encryption (BitLocker).

Users from Trey Research must be able to access App2 by using their credentials from treyresearch.com.
How to enable Certification Authority Auditing on Windows Server
By default, the Auditing function is not enabled on the CA server. After the auditing is enabled, all the events will be logged in the "Security log". To enable the auditing, I need to modify the following settings.
1. On the CA server, log in as Administrator
2. Launch "Certification Authority"
3. Right-click the name of the CA, select "Properties"
4. Select "Auditing" tab
5. Check the events, which you want to audit

6. Click "OK"
7. Launch "Local Group Policy editor"
8. Expand "Computer Configuration > Windows Settings > Security Settings > Local Policies > Audit Policy"
9. Double-click "Audit object access"
10. Check "Success" and "Failure"

NEW QUESTION: 2
次の各ステートメントについて、ステートメントがtrueの場合は、[はい]を選択します。それ以外の場合は、[いいえ]を選択します。
注：正しい選択はそれぞれ1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: No
The API determines the type of account to create. Azure Cosmos DB provides five APIs: Core (SQL) and MongoDB for document data, Gremlin for graph data, Azure Table, and Cassandra. Currently, you must create a separate account for each API.
Box 2: Yes
Azure Cosmos DB uses partitioning to scale individual containers in a database to meet the performance needs of your application. In partitioning, the items in a container are divided into distinct subsets called logical partitions. Logical partitions are formed based on the value of a partition key that is associated with each item in a container.
Box 3: No
Logical partitions are formed based on the value of a partition key that is associated with each item in a container.

NEW QUESTION: 3
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at test layer must meet the following requirements:
Data storage:
* Serve as a repository (or high volumes of large files in various formats.
* Implement optimized storage for big data analytics workloads.
* Ensure that data can be organized using a hierarchical structure.
Batch processing:
* Use a managed solution for in-memory computation processing.
* Natively support Scala, Python, and R programming languages.
* Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
* Support parallel processing.
* Use columnar storage.
* Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Languages: R, Python, Java, Scala, SQL
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is