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NEW QUESTION: 1
Refer to the exhibit. PC_1 is exchanging packets with the FTP server. Consider the packets as they leave RouterB interface Fa0/1 towards RouterA. Drag the correct frame and packet addresses to their place in the table.

Answer:
Explanation:

Explanation
Source Mac AddressDestination Mac AddressSource IP addressDestination MAC address MAC 0000.0c89.3333MAC 0000.0c89.9999 IP 172.16.34.250IP 172.16.21.7

NEW QUESTION: 2
The IT operations team wants to install IBM Tivoli Endpoint Manager (TEM) in a network where proxy Internet access is required. The proxy requires a non-Windows credential to be entered each time the Internet is accessed. Where is this registry key set: [HKEY_LOCAL_MACHINE\SOFTWARE\BigFix\Enterprise ServertGatherService]?
A. On the TEM server
B. On a client with direct Internet access
C. On the Top Level Relay
D. On the Internet DMZ relay
Answer: A

NEW QUESTION: 3
注：この質問は同じシナリオを使用する一連の質問の一部です。あなたの便宜のために、シナリオは各質問で繰り返されます。各質問はそれぞれ異なる目標と答えの選択を提示しますが、シナリオの本文はシリーズの各質問でまったく同じです。
繰り返しシナリオの開始
複数のクライアントアプリケーションをサポートするMicrosoft SQL Serverデータウェアハウスインスタンスがあります。
データウェアハウスには、Dimension.SalesTerritory、Dimension.Customer、Dimension.Date、Fact.Ticket、Fact.Orderの各テーブルがあります。 Dimension.SalesTerritoryテーブルとDimension.Customerテーブルは頻繁に更新されます。 Fact.Orderテーブルは毎週のレポート作成に最適化されていますが、会社はそれを毎日に変更したいと考えています。 FactOrderテーブルはETLプロセスを使用して読み込まれます。インデックスは時間の経過とともにテーブルに追加されましたが、これらのインデックスが存在するとデータのロードが遅くなります。
データウェアハウス内のすべてのデータは共有SANに保管されています。すべてのテーブルはDB1という名前のデータベースにあります。開発環境用の実動データのコピーを含む、DB2という名前の2番目のデータベースがあります。データウェアハウスは拡大し、ストレージのコストは増加しました。 1年を超えるデータはめったにアクセスされず、履歴と見なされます。
*データウェアハウスの管理性を向上させ、毎晩すべてのトランザクションデータを再作成する必要性を回避するためにテーブルパーティションを実装します。できるだけ細かいパーティション戦略を使用します。
*FactOrderテーブルを分割し、合計7年間のデータを保持します。
*Fact.Ticketテーブルを分割し、7年間のデータを保持します。毎月末に、パーティション構造はスライディングウィンドウ方式を適用して、次の月に新しいパーティションが使用可能になり、最も古い月のデータがアーカイブされて削除されるようにする必要があります。
*Dimension.SalesTerritory、Dimension.Customer、およびDimension.Dateテーブルのデータロードを最適化します。
*データベース内のすべてのテーブルを増分ロードし、すべての増分変更が確実に処理されるようにします。
*Fact.Orderパーティションのデータロード処理中のパフォーマンスを最大化します。
*履歴データをオンラインのままにしてクエリに使用できるようにします。
*現在のデータに対するクエリパフォーマンスを維持しながら、継続的なストレージコストを削減します。
クライアントアプリケーションを変更することは許可されていません。
繰り返しシナリオの終了
Dimension.SalesTerritory、Dimension.Customer、およびDimension.Dateテーブルのデータロードを最適化する必要があります。
各テーブルにどのテクノロジを使用する必要がありますか？
回答するには、回答領域で適切なテクノロジを選択してください。


Answer:
Explanation:

Explanation

Box 1: Temporal table
Box 2: Temporal table
Compared to CDC, Temporal tables are more efficient in storing historical data as it ignores insert actions.
Box 3: Change Data Capture (CDC)
By using change data capture, you can track changes that have occurred over time to your table. This kind of functionality is useful for applications, like a data warehouse load process that need to identify changes, so they can correctly apply updates to track historical changes over time.
CDC is good for maintaining slowly changing dimensions.
Scenario: Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date tables.
The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated.
References:
https://www.mssqltips.com/sqlservertip/5212/sql-server-temporal-tables-vs-change-data-capture-vs-change-track
https://docs.microsoft.com/en-us/sql/relational-databases/tables/temporal-table-usage-scenarios?view=sql-server

NEW QUESTION: 4
Your database instance is started with a PFILE.
Examine these parameters:

You want to increase the size of the buffer cache.
Free memory is available to increase the size of the buffer cache.
You execute the command:
SQL> ALTER SYSTEM SET DB_CACHE_SIZE=1024M;
What is the outcome?
A. Change is applied to the current instance, but does not persist after instance restart
B. The value is changed only in the PFILE and takes effect at the next instance startup
C. It fails because the SCOPE clause is missing
D. The value is changed for the current instance and in the PFILE
Answer: A
Explanation:
https://docs.oracle.com/database/121/SQLRF/statements_2017.htm#SQLRF00902