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質問 # 34
小売顧客はさまざまなソースから顧客データを取得したいと考えています
ID 解決を活用して、
セグメンテーションで使用されます。
これをアクティベーション メンバーシップとしてセグメント化する必要があるのはどのエンティティですか?
- A. 個人
- B. 統合連絡先
- C. 統合された個人
- D. 加入者
正解：C
解説：
The correct answer is B, Unified Individual. A Unified Individual is a record that represents a customer across different data sources, created by applying identity resolution rulesets. Identity resolution rulesets are sets of match and reconciliation rules that define how to link and merge data from different sources based on common attributes. Data Cloud uses identity resolution rulesets to resolve data across multiple data sources and helps you create one record for each customer, regardless of where the data came from1. A retail customer who wants to bring customer data from different sources and use identity resolution for segmentation should segment on the Unified Individual entity, which contains the resolved and consolidated customer data. The other options are incorrect because they do not represent the resolved customer data across different sources. A Subscriber is a record that represents a customer who has opted in to receive marketing communications. A Unified Contact is a record that represents a customer who has a relationship with a specific business unit. An Individual is a record that represents a customer's profile data from a single data source. References:
* Identity Resolution Ruleset Processing Results
* Consider Data Implications for Segmentation
* Prepare for your Salesforce Data Cloud Consultant Credential
* AI-based Identity Resolution: Linking Diverse Customer Data
質問 # 35
コンサルタントは、毎日評価される誕生日キャンペーンのセグメントを作成するためにどの演算子を使用する必要がありますか?
- A. の間にあります
- B. の記念日です
- C. 今日です
- D. 誕生日です
正解：B
解説：
To create a segment for a birthday campaign that is evaluated daily, the consultant should use the Is Anniversary Of operator. This operator compares a date field with the current date and returns true if the month and day are the same, regardless of the year. For example, if the date field is 1990-01-01 and the current date is 2023-01-01, the operator returns true. This way, the consultant can create a segment that includes all the customers who have their birthday on the same day as the current date, and the segment will be updated daily with the new birthdays. The other options are not the best operators to use for this purpose because:
A: The Is Today operator compares a date field with the current date and returns true if the date is the same, including the year. For example, if the date field is 1990-01-01 and the current date is
223-01-01, the operator returns false. This operator is not suitable for a birthday campaign, as it will only include the customers who were born on the same day and year as the current date, which is very unlikely.
B: The Is Birthday operator is not a valid operator in Data Cloud. There is no such operator available in the segment canvas or the calculated insight editor.
C: The Is Between operator compares a date field with a range of dates and returns true if the date is within the range, including the endpoints. For example, if the date field is 1990-01-01 and the range is
2022-12-25 to 2023-01-05, the operator returns true. This operator is not suitable for a birthday campaign, as it will only include the customers who have their birthday within a fixed range of dates, and the segment will not be updated daily with the new birthdays.
質問 # 36
ユーザーが Data Cloud で統合された顧客データを視覚化および分析できるようにするツールはどれですか?
- A. Tableau
- B. Einstein Analytics
- C. Heroku
- D. Salesforce CLI
正解：A
解説：
Salesforce Data Cloud Overview: Salesforce Data Cloud enables organizations to unify and manage customer data from multiple sources, providing a comprehensive view of customer interactions and behaviors.
Visualization and Analysis: For visualizing and analyzing this unified data, Salesforce provides multiple tools, each serving different purposes. Tableau is particularly noted for its advanced analytics and visualization capabilities.
Tableau Integration: Tableau is integrated with Salesforce, allowing users to create detailed and interactive visualizations. It can connect directly to Salesforce Data Cloud, pulling in unified data for comprehensive analysis.
Capabilities: Tableau supports a wide range of data sources and formats, offering drag-and-drop features to create complex charts and dashboards. This makes it an ideal tool for analyzing the rich datasets managed within Salesforce Data Cloud.
References:
* Salesforce Help: Tableau Integration
* Salesforce Data Cloud Overview
質問 # 37
ノーザン トレイル アウトフィッターズは、新しい顧客データを毎日 Amazon S3 バケットにアップロードして、データ クラウドに取り込みます。
新しくインポートされたデータを確実に準備して任意のセグメントで使用できるようにするには、各プロセスをどの順序で実行する必要がありますか?
- A. 計算されたインサイト > データ ストリームの更新 > ID 解決
- B. データ ストリームの更新 > 計算された分析情報 > ID 解決
- C. ID 解決 > データ ストリームの更新 > 計算された分析情報
- D. データ ストリームの更新 > ID 解決 > 計算された分析情報
正解：D
解説：
To ensure that freshly imported data from an Amazon S3 Bucket is ready and available to use for any segment, the following processes should be run in this order:
* Refresh Data Stream: This process updates the data lake objects in Data Cloud with the latest data from the source system. It can be configured to run automatically or manually, depending on the data stream settings1. Refreshing the data stream ensures that Data Cloud has the most recent and accurate data from the Amazon S3 Bucket.
* Identity Resolution: This process creates unified individual profiles by matching and consolidating source profiles from different data streams based on the identity resolution ruleset. It runs daily by default, but can be triggered manually as well2. Identity resolution ensures that Data Cloud has a single view of each customer across different data sources.
* Calculated Insight: This process performs calculations on data lake objects or CRM data and returns a result as a new data object. It can be used to create metrics or measures for segmentation or analysis purposes3. Calculated insights ensure that Data Cloud has the derived data that can be used for personalization or activation.
References:
* 1: Configure Data Stream Refresh and Frequency - Salesforce
* 2: Identity Resolution Ruleset Processing Results - Salesforce
* 3: Calculated Insights - Salesforce
質問 # 38
データ ストリームの削除を妨げる 2 つの依存関係はどれですか?
2 つの答えを選択してください
- A. 基礎となるデータ レイク オブジェクトはデータ モデル オブジェクトにマップされます。
- B. 基礎となるデータ レイク オブジェクトはデータ変換で使用されます。
- C. 基礎となるデータ レイク オブジェクトはセグメンテーションで使用されます。
- D. 基盤となるデータ レイク オブジェクトがアクティブ化に使用されます。
正解：A、B
解説：
To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a data stream from being deleted1:
* Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2.
* Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.
References:
* 1: Delete a Data Stream article on Salesforce Help
* 2: [Data Transforms in Data Cloud] unit on Trailhead
* 3: [Data Model in Data Cloud] unit on Trailhead
質問 # 39
製品ファミリーごとに機会の収益または数量を定義するデータ モデルのサブジェクト領域はどれですか?
- A. 製品
- B. 販売注文
- C. エンゲージメント
- D. パーティー
正解：B
解説：
The Sales Order subject area defines the details of an order placed by a customer for one or more products or services. It includes information such as the order date, status, amount, quantity, currency, payment method, and delivery method. The Sales Order subject area also allows you to track the revenue or quantity for an opportunity by product family, which is a grouping of products that share common characteristics or features.
For example, you can use the Sales Order Line Item DMO to associate each product in an order with its product family, and then use the Sales Order Revenue DMO to calculate the total revenue or quantity for each product family in an opportunity. References: Sales Order Subject Area, Sales Order Revenue DMO Reference
質問 # 40
ノーザン トレイル アウトフィッターズは、データ クラウド インスタンスで個人を統合します。
CA コンサルタントが統合プロファイルのデータを検証するために使用する 3 つの機能はどれですか?
3 つの答えを選択してください
- A. ID 解決
- B. プロファイル エクスプローラー
- C. APL のクエリ
- D. データ エクスプローラー
- E. データアクション
正解：A、B、D
解説：
To validate the data on a unified profile, the consultant can use the following features:
* Identity Resolution: This feature allows the consultant to view and edit the identity resolution rulesets that determine how individuals are unified from different data sources1.
* Data Explorer: This feature allows the consultant to browse and filter the unified profiles and view their attributes, segments, and activities2.
* Profile Explorer: This feature allows the consultant to drill down into a specific unified profile and view its details, such as source records, identity graph, calculated insights, and data actions3. References:
* 1: Identity Resolution in Data Cloud
* 2: Data Explorer in Data Cloud
* 3: Profile Explorer in Data Cloud
質問 # 41
顧客にとってのデータクラウドの主な価値は何ですか?
- A. すべての匿名データに対する単一の信頼できる情報源を作成するには
- B. すべてのシステムをゴールデン レコードで接続するには
- C. 顧客の行動を聞き、理解し、それに基づいて行動することで、パーソナライズされたキャンペーンを作成するため
- D. 顧客とその関連データの統合ビューを提供するため
正解：D
解説：
Data Cloud is a platform that enables you to activate all your customer data across Salesforce applications and other systems. Data Cloud allows you to create a unified profile of each customer by ingesting, transforming, and linking data from various sources, such as CRM, marketing, commerce, service, and external data providers. Data Cloud also provides insights and analytics on customer behavior, preferences, and needs, as well as tools to segment, target, and personalize customer interactions. Data Cloud's primary value to customers is to provide a unified view of a customer and their related data, which can help you deliver better customer experiences, increase loyalty, and drive growth. References: Salesforce Data Cloud, When Data Creates Competitive Advantage
質問 # 42
コンサルタントは、以前に黒のパンツを購入した顧客向けに新製品の発売を発表するセグメントを構築しています。
この基準を満たすために、コンサルタントは Order Product オブジェクトから製品の色と製品タイプの属性をどのように配置する必要がありますか?
- A. 製品の色と製品タイプの属性を 1 つのコンテナに配置します。
- B. 動的に適用する「黒」の計算された分析情報の属性を配置します。
- C. 製品および製品タイプの属性を直接属性として配置します。
- D. 製品の色の属性を 1 つのコンテナに配置し、製品タイプの属性を別のコンテナに配置します。
正解：A
解説：
To create a segment based on the product color and product type from the Order Product object, the consultant should place the attributes for product color and product type in a single container. This way, the segment will include only the customers who have purchased black pants, and not those who have purchased black shirts or blue pants. A container is a grouping of attributes that defines a segment of individuals based on a logical AND operation. Placing the attributes in separate containers would result in a segment that includes customers who have purchased any black product or any pants product, which is not the desired criteria. Placing an attribute for the "black" calculated insight would not work, because calculated insights are based on aggregated data and not individual-level data. Placing the attributes as direct attributes would not work, because direct attributes are used to filter individuals based on their profile data, not their order data. References:
* Create a Segment in Data Cloud
* Learn About Segmentation Tools
* Salesforce Launches: Data Cloud Consultant Certification
質問 # 43
Cumulus Financial の採用チームは、どの候補者が過去 24 時間以内に Web サイトの求人ページを少なくとも 2 回閲覧したかを特定したいと考えています。彼らは、これらの候補者に関する情報を Data Cloud でのセグメント化に利用できるようにし、候補者を採用システムに追加したいと考えています。
この目標を達成するには、コンサルタントはどの機能を推奨する必要がありますか?
- A. ストリーミングの分析情報
- B. バッチバタ変換
- C. 計算された洞察
- D. ストリーミング データ変換
正解：A
解説：
A streaming insight is a feature that allows users to create and monitor real-time metrics from streaming data sources, such as web and mobile events. A streaming insight can also trigger data actions, such as sending notifications, creating records, or updating fields, based on the metric values and conditions. Therefore, a streaming insight is the best feature to achieve the goal of identifying candidates who have browsed the jobs page on the website at least twice within the last 24 hours, and adding them to the recruiting system. The other options are incorrect because:
* A streaming data transform is a feature that allows users to transform and enrich streaming data using SQL expressions, such as filtering, joining, aggregating, or calculating values. However, a streaming data transform does not provide the ability to monitor metrics or trigger data actions based on conditions.
* A calculated insight is a feature that allows users to define and calculate multidimensional metrics from data using SQL expressions, such as LTV, CSAT, or average order value. However, a calculated insight is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data actions.
* A batch data transform is a feature that allows users to create and schedule complex data transformations using a visual editor, such as joining, aggregating, filtering, or appending data.
However, a batch data transform is not suitable for real-time data analysis, as it runs on a scheduled basis and does not support data actions. References: Streaming Insights, Create a Streaming Insight, Use Insights in Data Cloud, Learn About Data Cloud Insights, Data Cloud Insights Using SQL, Streaming Data Transforms, Get Started with Batch Data Transforms in Data Cloud, Transformations for Batch Data Transforms, Batch Data Transforms in Data Cloud: Quick Look, Salesforce Data Cloud: AI CDP.
質問 # 44
データ クラウド コンサルタントが、企業のデータ クラウド ライフサイクルの初期フェーズを評価しています。
データ クラウド ライフサイクルを効果的に開始するには、どのアクションが不可欠ですか?
- A. 既存のデータを Customer 360 データ モデルに移行します。
- B. ユースケースと必要なデータ ソースおよびデータ品質を特定します。
- C. データを分析し、データ スペースに分割します。
- D. 計算された洞察を使用して、この会社にとっての Data Cloud の利点を判断します。
正解：B
解説：
Data Cloud Lifecycle: The initial phase of the Salesforce Data Cloud lifecycle is critical for setting the foundation for successful data integration and utilization.
Identifying Use Cases:
* Importance: Defining clear use cases helps in understanding the business objectives and how Data Cloud can address them.
* Required Data Sources: Identifying the necessary data sources ensures that relevant data is ingested into Data Cloud.
* Data Quality: Assessing data quality is essential for accurate and reliable data analysis and insights.
Actions:
* Step 1: Engage with stakeholders to define specific use cases for Data Cloud.
* Step 2: Identify and catalog the required data sources for these use cases.
* Step 3: Evaluate the quality of data from these sources to ensure they meet the standards for effective data analysis.
References:
* Salesforce Data Cloud Implementation Guide
* Salesforce Data Cloud Lifecycle
質問 # 45
コンサルタントは、販売注文データを Data Cloud に接続し、プロファイル、エンゲージメント、その他のカテゴリのどれを使用して DLO をマッピングするかを検討しています。コンサルタントは、エンゲージメント カテゴリを使用して、Order-Headers という DLO を Sales Order DMO にマッピングすることを選択します。
このアクションは将来のマッピングにどのような影響を与えますか?
- A. プロファイル DLO を販売注文 DMO にマッピングすると、カテゴリがプロファイルに更新されます。
- B. エンゲージメント カテゴリの DLO は、プロファイル、エンゲージメント、またはその他のカテゴリを使用して任意の DMO にマッピングできます。
- C. エンゲージメント カテゴリ DLO のみを販売注文 DMO にマップできます。販売注文はエンゲージメント カテゴリに割り当てられます。
- D. プロファイル DLO をマッピングすると、販売注文 DMO がプロファイル カテゴリとエンゲージメント カテゴリの両方に割り当てられます。
正解：C
解説：
Data Lake Objects (DLOs) and Data Model Objects (DMOs): In Salesforce Data Cloud, DLOs are mapped to DMOs to organize and structure data. Categories like Profile, Engagement, and Other define how these mappings are used.
Engagement Category: Mapping a DLO to the Engagement category indicates that the data is related to customer interactions and activities.
Impact on Future Mappings:
* Engagement Category Restriction: When a DLO like Order-Headers is mapped to the Sales Order DMO under the Engagement category, future mappings of the Sales Order DMO are restricted to Engagement category DLOs.
* Category Assignment: The Sales Order DMO is assigned to the Engagement category, meaning only DLOs categorized as Engagement can be mapped to it in the future.
Benefits:
* Consistency: Ensures consistent data categorization and usage, aligning data with its intended purpose.
* Accuracy: Helps in maintaining the integrity of data mapping and ensures that engagement-related data is accurately captured and utilized.
References:
* Salesforce Data Cloud Mapping
* Salesforce Data Cloud Categories
質問 # 46
データ クラウド コンサルタントは、新しいサービスベースのデータ ソースのデータ ストリームをセットアップ中です。
ケースデータを取り込む場合、どのフィールドをイベント時間フィールドに関連付けることが推奨されますか?
- A. エスカレーション日
- B. 解決日
- C. 最終更新日
- D. 作成日
正解：C
解説：
The Event Time field is a special field type that captures the timestamp of an event in a data stream. It is used to track the chronological order of events and to enable time-based segmentation and activation. When ingesting Case data, the recommended field to be associated with the Event Time field is the Last Modified Date field. This field reflects the most recent update to the case and can be used to measure the case duration, resolution time, and customer satisfaction. The other fields, such as Resolution Date, Escalation Date, or Creation Date, are not as suitable for the Event Time field, as they may not capture the latest status of the case or may not be applicable for all cases. References: Data Stream Field Types, Salesforce Data Cloud Exam Questions
質問 # 47
計算された洞察がセグメンテーション キャンバスに表示されるために満たす必要がある 2 つの要件はどれですか?
2 つの答えを選択してください
- A. 計算されたインサイトには、個人または統合個人 ID を含むディメンションが含まれている必要があります。
- B. セグメント化されたテーブルの主キーは、計算されたインサイトのメトリックである必要があります。
- C. セグメント化されたテーブルの主キーは、計算されたインサイトのディメンションである必要があります。
- D. 計算されたインサイトのメトリクスには数値のみを含める必要があります。
正解：A、C
解説：
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas.
There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location.
The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud.
The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
References: Create a Calculated Insight, Use Insights in Data Cloud, Segmentation
質問 # 48
ユーザーは Data Cloud にセグメントを構築し、アクティベーションを作成中です。関連する属性を選択するときに、個人に関連するとわかっている特定の属性セットを見つけることができません。
これらの属性が使用できない理由を説明しているのはどれですか?
- A. セグメントはプロファイル データでセグメント化されていません。
- B. アクティベーションには 1 対 1 の属性のみを含めることができます。
- C. 必要な属性は、異なる関連パス上に存在します。
- D. 属性は別のアクティベーションで使用されています。
正解：C
解説：
The correct answer is C, the desired attributes reside on different related paths. When creating an activation in Data Cloud, you can select related attributes from data model objects that are linked to the segment entity.
However, not all related attributes are available for every activation. The availability of related attributes depends on the container path, which is the sequence of data model objects that connects the segment entity to the related entity. For example, if you segment on the Unified Individual entity, you can select related attributes from the Order Product entity, but only if the container path is Unified Individual > Order > Order Product. If the container path is Unified Individual > Order Line Item > Order Product, then the related attributes from Order Product are not available for activation. This is because Data Cloud only supports one-to-many relationships for related attributes, and Order Line Item is a many-to-many junction object between Order and Order Product. Therefore, you need to ensure that the desired attributes reside on the same related path as the segment entity, and that the path does not include any many-to-many junction objects. The other options are incorrect because they do not explain why the related attributes are not available. The segment entity can be any data model object, not just profile data. The attributes are not restricted by being used in another activation. Activations can include one-to-many attributes, not just one-to-one attributes. References:
* Related Attributes in Activation
* Considerations for Selecting Related Attributes
* Salesforce Launches: Data Cloud Consultant Certification
* Create a Segment in Data Cloud
質問 # 49
ノーザン トレイル アウトフィッターズは、Marketing Cloud データの一部を Data Cloud で使用したいと考えています。
どのエンゲージメント チャネル データにカスタム統合が必要ですか?
- A. SMS
- B. クラウドページ
- C. 電子メール
- D. モバイルプッシュ
正解：B
解説：
CloudPage is a web page that can be personalized and hosted by Marketing Cloud. It is not one of the standard engagement channels that Data Cloud supports out of the box. To use CloudPage data in Data Cloud, a custom integration is required. The other engagement channels (SMS, email, and mobile push) are supported by Data Cloud and can be integrated using the Marketing Cloud Connector or the Marketing Cloud API. References: Data Cloud Overview, Marketing Cloud Connector, Marketing Cloud API
質問 # 50
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