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NEW QUESTION: 1
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、指定された目標を達成できる独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合がありますが、他の質問セットには正しい解決策がない場合があります。
このシナリオで質問に回答した後は、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
100 GBのファイルを含むAzureストレージアカウントがあります。ファイルにはテキストと数値が含まれています。
行の75％には、平均長が1.1 MBの説明データが含まれています。
Azure Synapse Analyticsでストレージアカウントからエンタープライズデータウェアハウスにデータをコピーする予定です。
データが迅速にコピーされるようにするには、ファイルを準備する必要があります。
解決策：ファイルを圧縮区切りテキストファイルに変換します。
これは目標を達成していますか？
A. いいえ
B. はい
Answer: B
Explanation:
All file formats have different performance characteristics. For the fastest load, use compressed delimited text files.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data

NEW QUESTION: 2
回帰分析、故障モードと影響分析（FMEA）、フォールトツリー分析（FTA）、および傾向分析は、どのツールまたは手法の例ですか？
A. 専門家の判断
B. 予測方法
C. 分析手法
D. アーンドバリューマネジメント
Answer: C

NEW QUESTION: 3
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have a Microsoft SQL Server data warehouse instance that supports several client applications.
The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.
All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.
You have the following requirements:
* Implement table partitioning to improve the manageability of the data warehouse and to avoid the need to repopulate all transactional data each night. Use a partitioning strategy that is as granular as possible.
* Partition the Fact.Order table and retain a total of seven years of data.
* Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest month of data is archived and removed.
* Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date tables.
* Incrementally load all tables in the database and ensure that all incremental changes are processed.
* Maximize the performance during the data loading process for the Fact.Order partition.
* Ensure that historical data remains online and available for querying.
* Reduce ongoing storage costs while maintaining query performance for current data.
You are not permitted to make changes to the client applications.
You need to implement the data partitioning strategy.
How should you partition the Fact.Order table?
A. Create 2,557 partitions.
B. Create 17,520 partitions.
C. Create 730 partitions.
D. Use a granularity of two days.
Answer: A
Explanation:
We create on partition for each day. 7 years times 365 days is 2,555. Make that 2,557 to provide for leap years.
From scenario: Partition the Fact.Order table and retain a total of seven years of data.
Maximize the performance during the data loading process for the Fact.Order partition.

NEW QUESTION: 4
An integrator is installing a DL380 Gen9 server for a customer who will be using this server for their large data base. The customer needs maximum memory capacity. Which type of HP memory should the integrator choose?
A. LRDIMMs
B. NVDIMMs
C. Hybrid DIMMs
D. RDIMMs
Answer: A