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NEW QUESTION: 1
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You have a Microsoft SQL Server Analysis Services (SSAS) instance that is configured to use multidimensional mode. You create the following cube:

Users need to be able to analyze sales by product and color.
You need to create the dimension.
Which relationship type should you use between the InternetSales table and the new dimension?
A. many-to-many
B. data mining
C. referenced
D. fact
E. regular
F. no relationship
Answer: C
Explanation:
Explanation/Reference:
Explanation:
A reference dimension relationship between a cube dimension and a measure group exists when the key column for the dimension is joined indirectly to the fact table through a key in another dimension table, as shown in the following illustration.

A reference dimension relationship represents the relationship between dimension tables and a fact table in a snowflake schema design. When dimension tables are connected in a snowflake schema, you can define a single dimension using columns from multiple tables, or you can define separate dimensions based on the separate dimension tables and then define a link between them using the reference dimension relationship setting. The following figure shows one fact table named InternetSales, and two dimension tables called Customer and Geography, in a snowflake schema.

You can create two dimensions related to the InternetSales measure group: a dimension based on the Customer table, and a dimension based on the Geography table. You can then relate the Geography dimension to the InternetSales measure group using a reference dimension relationship using the Customer dimension.
Incorrect Answers:
B: A regular dimension relationship between a cube dimension and a measure group exists when the key column for the dimension is joined directly to the fact table.
C: Fact dimensions, frequently referred to as degenerate dimensions, are standard dimensions that are constructed from attribute columns in fact tables instead of from attribute columns in dimension tables.
E: Many to Many Dimension Relationships.
In most dimensions, each fact joins to one and only one dimension member, and a single dimension member can be associated with multiple facts. In relational database terminology, this is referred to as a one-to-many relationship. However, it is frequently useful to join a single fact to multiple dimension members. For example, a bank customer might have multiple accounts (checking, saving, credit card, and investment accounts), and an account can also have joint or multiple owners. The Customer dimension constructed from such relationships would then have multiple members that relate to a single account transaction.

References: https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models-olap-logical- cube-objects/dimension-relationships

NEW QUESTION: 2
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.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You need to configure storage management for the accounting department.
What should you do?
A. Set the Site Collection Storage Management settings to Manual.
B. Change the properties of the Accounting site collection.
C. Set the SharePoint admin center experience setting to Use Advanced.
D. Set the Show or Hide Options setting for Sites to Show.
Answer: A
Explanation:
Explanation/Reference:
References: https://support.office.com/en-us/article/Manage-site-collection-storage-limits-77389c2c-8e7e-
4b16-ab97-1c7103784b08

NEW QUESTION: 3
ソリューションアーキテクトは、顧客の活動に関するデータを保存するAmazon DynamoDBテーブルを設計する必要があります。このデータは、最近の顧客の行動を分析するために使用されるため、1週間以内のデータは頻繁にアクセスされ、古いデータはまれにしかアクセスされません。 1か月以上前のデータをアプリケーションで参照する必要はありませんが、年末の分析のためにアーカイブする必要があります。
これらの要件を満たす最もコスト効率の高い方法は何ですか？ （2つ選択してください。）
A. AWS Data Pipelineを使用して、DynamoDBからAmazon S3に古いテーブルデータをエクスポートし、古いテーブルを削除します。
B. より高い書き込み容量ユニットをプロビジョニングして、パーティションの数を最小限にします。
C. データを前処理して複数のレコードを統合し、書き込み操作を最小限にします。
D. DynamoDBの有効期間設定を使用して、特定の期間後にアイテムを期限切れにします。
E. 各週のデータに対して個別のテーブルを作成し、現在の週のスループットを高めます。
Answer: A,E
Explanation:
AWS Data Pipeline is a web service that you can use to automate the movement and transformation of data. With AWS Data Pipeline, you can define data-driven workflows, so that tasks can be dependent on the successful completion of previous tasks. You define the parameters of your data transformations and AWS Data Pipeline enforces the logic that you've set up.
https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/what-is-datapipeline.html
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/best-practices.html

NEW QUESTION: 4
A sales manager needs to set up goals in Dynamics 365 Sales for salespeople.
The measurement of goals must be based on the total deal amount upon closing an opportunity.
The fiscal year for the goals must be based on the calendar year.
You need to create the rollup query for the goal metrics.
Which options should you select? To answer,select the appropriate options in the answer area.
NOTE:Each correct selection is worth one point.

Answer:
Explanation:

Explanation