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MB-260 New Dumps Pdf | Latest Microsoft MB-260: Microsoft Customer Data Platform Specialist
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Microsoft Customer Data Platform Specialist Sample Questions (Q36-Q41):
NEW QUESTION # 36
You are a Customer Data Platform Specialist. You completed unification and are looking to create relevant segments for your business. You want to identify insights on fields that overlap between segments.
Which statement is correct about using segment overlap?
- A. Audience insights will recommend which fields may be the most insightful to use for segment overlap analysis.
- B. Audience insights will automatically select the fields for overlap analysis when you create a new segment overlap.
- C. You can select one or more fields to analyze for overlap analysis when you create a new segment overlap.
- D. You can select up to three fields to analyze for overlap analysis when you create a new segment overlap.
Answer: C
Explanation:
Reference:
https://docs.microsoft.com/en-us/dynamics365/customer-insights/audience-insights/segment-insights
NEW QUESTION # 37
You are a Customer Data Platform Specialist. The marketing team requested that customer cellphone numbers be added to the customer profile in audience insights. The customer cellphone numbers are stored in a separate table in the Azure Gen 2 Storage Account.
You decide to create the data source(s) needed in audience insights.
Which statements best describes the steps needed to ingest the required data to audience insights?
- A. In audience insights, under Data, select Data Sources, add data source and select Azure data lake storage as an import method, enter name as "Loyalty Cell Phone' and enter storage account name to authenticate. Repeat the steps for other tables.
- B. In audience insights, add data source and select Azure data lake storage as an import method, enter
"cellPhoneJoyalty1 as a data source name, and then enter the container name and method to authenticate. Repeat the same steps for other tables. - C. In audience insights, add data source and select Microsoft Dataverse as an import method, enter
"CellPhoneloyalty" as a data source name. - D. In audience insights, select Data Sources, add data source, enter "CellPhone" in the name field and click Next.
Answer: B
Explanation:
There are three data sources containing customer profile data loaded to a dedicated storage account and container in the Azure Data Lake.
* Ingesting Cell phone data- the requirement is to keep the name of the date sources aligned with the design document.
cellPhone_loyaly.csv: srcid (primary key), cellphone
Reference:
https://docs.microsoft.com/en-us/dynamics365/customer-insights/audience-insights/connect-power-query
Topic 1, Adventure Works
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question.
General Overview
AdventureWorks Cycles is a bicycle retailer with a few locations in the Midwest region. The AdventureWorks Cycles business model supports both in store purchases as well as online orders. In addition to offering a wide variety of bicycles, the company sells clothing, performance nutrition supplements, bicycle parts as well as bicycle fitting and repair services. The customer base varies from professional cyclists, individual leisure riders to families. The business experienced unprecedented growth of over 2000% during the pandemic bringing a total number of customers to 10,000. The company decided to invest in Microsoft Dynamics 365 Customer Insights and Dynamics 365 Sales App to unify customer data and improve sales.
Blue Yonder Airlines created a new division named BY Excursions (BYE). BYE operates site-seeing tours arid other excursions in vacation destinations across North America.
BYE is the product of the acquisition of three regional tour and excursion companies.
* Each of these regional operations have updated their branding.
* The three operations continue to maintain separate CRM systems for sales and customer service in their respective terntones (East West and Central).
* Each regional operator offers different types of tours and excursions. For example, the East region currently offers boat tours, but the Central region does not.
BYE uses a single instance of Dynamics 365 Marketing for marketing automation, and tt recently implemented Dynamics 365 Customer Insights as its CDP. Dynamics 365 Marketing and Customer Insights are not currently connected.
A corporate data lake is built on Azure Data Lake Gen 2. This data lake has two containers named 'imports- and "exports. - The BYE data science team uses Azure Machine Learning Studio to build predictive models.
An Azure Data Factory pipeline produces flat-fit
le extracts of all customers, events, and survey response data from every regional CRM system, and copies them to the corporate data lake imports container daily. These extracts are produced in pipe-delimited text format and each type of extract file has the same schema. The pipeline runs at 1 a.m. US Eastern Standard Time (UTC -5). Each regional system extract has the same format.
Customer data is represented as records in the Customer extract file. This file contains customer address and contact information. Because customers can make purchases in more than one region, the same customer may be represented in multiple regional extract files.
Regional extracts may also contain multiple records corresponding to the same individual customer.
Each record in a single regional extract will have a unique customer number value. The customer number value is not guaranteed to be unique across all regional extracts. Each customer file contains fewer than 50,000 records.
Customer event ticket purchases are represented as records in the event tickets extract file. This file contains a unique ID value for every ticket purchase along with details such as event type, event date, purchase date and ticket cost Each customer is also sent a customer satisfaction survey after the conclusion of every event. The survey includes numeric rating of 1 -5 (1 being le sati d and 5 being most satisfied) and a free-text response field for the customers to share their impressions of the event.
The schema for the three files in each extract is shown below:
Your team is responsible for the configuration of Customer insights. You are an Administrator in the environment.
Your team has configured a separate data source corresponding to the customer file extracts from each regional operation. Each data source uses a Microsoft Power Query text file connector to ingest the extract files. The Microsoft Enhanced Addresses enrichment has been enabled for each regional data source. The enrichment name for each region is the region name (East. West or Central) followed by "addresses." Your team has also configured a fourth data source using Power Query to create consolidated files containing all event tickets and survey response records. These two new files have the same layout as the regional files.
Customer email addresses are included in these files because customer numbers are not unique across regions.
Your team has defined a Unified Customer Profile based on the three different customer extract files. The East and West regional customer extracts have deduplication rules configured with the default merge preferences and the following centric:
1. Exact matches on LastName. HomeAddress, City and PostalCode.
2. Exact matches on FirstName, LastName, EmailAddress and normalized PhoneNumber.
The Central regional customer extract does not have any deduplication rules configured.
Your team has configured matching to start with the East region customer extract as the primary entity, then the Central region, then the West region. Each regional entity is configured to include all records, and subsequent entities match the previous entity using the following conditions:
1. Exact matches on LastName and normalized PhoneNumber.
2. Exact matches on normalized Phonernumber, EmailAddress and Country.
Your team has added activities based on the event ticket and survey response extracts. Survey responses have been semantical
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