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Question 1Get started with Dynamics 365 Customer Insights - Data

A data analyst is exploring Dynamics 365 Customer Insights - Data for the first time and wants to understand the primary purpose of the application. Which statement best describes what Customer Insights - Data is designed to do?

  1. Replace the organization's general ledger and financial reporting processes
  2. Provide a code repository and continuous integration pipeline for developers
  3. Unify customer data from multiple sources into a single customer profile for insight and activation Correct answer.
  4. Manage field service work orders and technician scheduling across regions

Explanation

Customer Insights - Data ingests data from many systems, resolves records into unified customer profiles, and enriches those profiles so teams can analyze and activate them. It is a customer data platform rather than an ERP, field service, or developer tooling product.

Question 2Get started with Dynamics 365 Customer Insights - Data

An organization wants to combine loyalty data, e-commerce transactions, and service tickets so that each customer appears once with a consolidated view. Which core capability of Customer Insights - Data delivers this outcome?

  1. Data unification through ingestion, mapping, matching, and merging Correct answer.
  2. Real-time chat routing for contact center agents
  3. Role-based security trimming of model-driven app forms
  4. Power Automate approval workflows for purchase requisitions

Explanation

Unification is the process that ingests source data, maps fields to a common schema, matches records across sources, and merges them into one unified customer profile. The other choices describe unrelated platform features.

Question 3Get started with Dynamics 365 Customer Insights - Data

A marketing team wants to segment customers by total lifetime spend and by preferred store location. Which part of Customer Insights - Data should they use to define and explore those groups?

  1. The data ingestion wizard, which only loads raw source tables
  2. The system job history page, which lists background processing runs
  3. The environment settings page, which configures retention periods
  4. Segments, which let users build rules or use measures over unified profiles Correct answer.

Explanation

Segments are created from unified customer profiles using rule-based logic, measures, or AI-assisted suggestions, and they power analysis and activation. Ingestion, job history, and settings support the platform but do not define audience groups.

Question 4Get started with Dynamics 365 Customer Insights - Data

Which statement accurately describes the relationship between a customer profile and the source records that contribute to it in Customer Insights - Data?

  1. A unified profile is built from one or more source records that are matched and merged together Correct answer.
  2. A unified profile is created manually by an administrator typing customer details
  3. A unified profile only contains data from the most recently ingested source
  4. A unified profile always corresponds to exactly one source record from one system

Explanation

Unification matches records that likely represent the same person or entity and merges them into a single profile that can draw attributes from several sources. Profiles are therefore the product of matching and merging, not of manual entry or a single system.

Question 5Get started with Dynamics 365 Customer Insights - Data

A company wants to send unified customer segments to an advertising platform and to a marketing email tool. Which capability of Customer Insights - Data supports this?

  1. Exports and connections that activate segments to external destinations Correct answer.
  2. The data source connection used to ingest CSV files
  3. The activity log that records user sign-ins
  4. The matching policy editor used during deduplication

Explanation

Activation is achieved through exports and connections that push segment membership and profile data to destinations such as advertising or email platforms. Matching policies and ingestion connections operate on inbound data rather than outbound activation.

Question 6Get started with Dynamics 365 Customer Insights - Data

Which Microsoft product family does Dynamics 365 Customer Insights - Data belong to, and what does that imply for licensing?

  1. It is included at no cost with every Microsoft 365 E3 subscription
  2. It is licensed only through perpetual on-premises server licenses
  3. It is a Dynamics 365 application, so access requires an appropriate Customer Insights license Correct answer.
  4. It is a free add-on bundled with Azure DevOps organization accounts

Explanation

Customer Insights - Data is part of the Dynamics 365 family and requires appropriate licensing for the users and capacity that consume it. It is not a free inclusion in general productivity subscriptions and is delivered as a cloud service.

Question 7Get started with Dynamics 365 Customer Insights - Data

During unification, an administrator must decide which fields from two source systems should be compared to determine whether two records represent the same customer. Which configuration element controls this?

  1. Relationship definitions used for hierarchy browsing in the UI
  2. Export destinations that define where segments are delivered
  3. Measures that aggregate transaction amounts per customer
  4. Match rules that specify the fields and normalization used for comparison Correct answer.

Explanation

Match rules define the fields, normalization, and precision used to decide whether records are duplicates, and they drive the matching stage of unification. Export destinations, measures, and hierarchy relationships serve different purposes.

Question 8Get started with Dynamics 365 Customer Insights - Data

Two source systems store phone numbers with different formats, one with country codes and one without. An administrator wants matching to treat these consistently. What should the administrator configure?

  1. Normalization settings on the match rule for the phone field Correct answer.
  2. A measure that counts distinct phone number strings
  3. A separate export for each phone number format
  4. A segment rule that filters out records lacking country codes

Explanation

Match rules include normalization options such as removing spaces, punctuation, or country codes so that equivalent values compare as equal. Filtering records or counting strings does not make formats comparable during matching.

Question 9Get started with Dynamics 365 Customer Insights - Data

After matching, several source records for the same customer contain conflicting values for city and email address. What does the merge configuration in Customer Insights - Data determine?

  1. Which users are allowed to view the segment editor
  2. Which source value wins for each field when records are consolidated Correct answer.
  3. Whether the customer profile is deleted from the environment
  4. How often the ingestion refresh job runs

Explanation

Merge policies define field-level precedence so that when matched records disagree, a consistent winning value is chosen for the unified profile. They do not control deletion, job scheduling, or user permissions.

Question 10Get started with Dynamics 365 Customer Insights - Data

An analyst needs to know how many unified customer profiles currently exist and which sources contributed to a specific profile. Where can this information be reviewed in Customer Insights - Data?

  1. In the export destination configuration page
  2. In the environment capacity settings page
  3. In the customer profiles area, which lists unified profiles and their contributing records Correct answer.
  4. In the match rule precision slider

Explanation

The customer profiles experience lists unified profiles and shows details such as which source records were merged into a given profile. Export configuration, match precision, and capacity settings do not present profile-level lineage.

Question 11Get started with Dynamics 365 Customer Insights - Data

A team wants to define a segment of customers who spent more than 500 in the last 90 days, using transaction data that has been related to unified profiles. Which approach fits best?

  1. Change the merge policy to prefer transaction amounts
  2. Edit the match rule to exclude low-value customers
  3. Build a segment rule that references a measure or related activity attribute Correct answer.
  4. Create a new data source connection for each transaction row

Explanation

Segments can reference measures and related activity attributes so that conditions like recent spend thresholds are evaluated against unified profiles. Match rules and merge policies shape unification and do not define audience criteria.

Question 12Get started with Dynamics 365 Customer Insights - Data

An administrator wants the unified profiles to refresh automatically each night after source data is updated. Which configuration should the administrator review?

  1. The refresh schedule configured for the data sources and unification process Correct answer.
  2. The user's personal time zone setting
  3. The segment membership expiration date
  4. The export destination authentication method

Explanation

Refresh schedules determine when ingestion and downstream unification run so that profiles reflect current source data. Expiration dates, destination authentication, and time zone preferences do not drive the refresh cadence.

Question 13Get started with Dynamics 365 Customer Insights - Data

A customer appears twice in the unified profiles because the match rule was too strict. What is the most appropriate first step to improve matching?

  1. Delete one of the duplicate source systems entirely
  2. Remove all measures from the environment
  3. Adjust the match rules to include additional or normalized fields with appropriate precision Correct answer.
  4. Disable unification and merge records by hand each week

Explanation

When matching is too strict, refining match rules by adding discriminating fields or normalization and tuning precision lets more true duplicates be detected. Deleting sources or manual merging does not scale and measures are unrelated to matching.

Question 14Get started with Dynamics 365 Customer Insights - Data

A retailer notices that unrelated customers are being merged into single profiles after a new source is added. Which explanation is most plausible?

  1. The export destination is misconfigured for the new source
  2. The match rule relies on a low-selectivity field such as a shared default phone value Correct answer.
  3. The environment has reached its storage capacity limit
  4. The segment refresh interval is set too short

Explanation

Over-merging typically results from match rules that compare fields with low uniqueness, causing many records to appear identical. Export configuration, refresh intervals, and storage limits affect delivery, timing, and capacity rather than record similarity.

Question 15Get started with Dynamics 365 Customer Insights - Data

Before activating a segment to an external advertising platform, a compliance officer asks what data will leave the environment. What determines the fields sent in that export?

  1. The data source ingestion schedule
  2. The match rule precision threshold
  3. The export configuration, including the destination and the attributes mapped to it Correct answer.
  4. The merge policy field precedence order

Explanation

Each export defines its destination and the attributes included, so the export configuration determines exactly what data leaves the environment. Matching, merging, and ingestion settings shape internal profiles but not outbound payload content.

Question 16Get started with Dynamics 365 Customer Insights - Data

An organization wants to enrich unified profiles with brand affinity and demographic attributes purchased from a third-party provider without building custom code. Which approach aligns with Customer Insights - Data capabilities?

  1. Use the built-in enrichment capability to attach third-party attributes to unified profiles Correct answer.
  2. Write a plugin that modifies profile records during the merge step
  3. Store enrichment attributes only in the original source system
  4. Replace unification with a spreadsheet maintained by the marketing team

Explanation

Enrichment features let organizations augment unified profiles with additional attributes from supported providers, and those attributes become available for segments and measures. Custom plugins, manual spreadsheets, and source-only storage do not deliver enrichment into the unified profile.

Question 17Get started with Dynamics 365 Customer Insights - Data

A data engineer must load data from a cloud data warehouse on a recurring basis. Which sequence reflects the intended flow in Customer Insights - Data?

  1. Configure exports first, then ingest data to fill the destinations
  2. Create a data source, ingest the data, unify it into profiles, then use segments and exports Correct answer.
  3. Create segments first, then ingest source data to populate them
  4. Run measures first, then define data sources that reference those measures

Explanation

The platform follows an ingest, unify, analyze, and activate progression: sources feed unification, and unified profiles support segments, measures, and exports. Later stages depend on earlier data being present, so starting with segments or exports is not workable.

Question 18Get started with Dynamics 365 Customer Insights - Data

A company wants to measure average order value per unified customer and then use that value as a segment condition. Which combination of features supports this requirement?

  1. A refresh schedule, referenced by a hierarchy relationship
  2. A match rule with high precision, referenced by an export destination
  3. A measure defined over related activity data, referenced by a segment rule Correct answer.
  4. A merge policy, referenced by a data source connection

Explanation

Measures compute aggregates such as average order value from related activity, and segment rules can reference those measures as conditions. Match rules, merge policies, and refresh schedules do not produce per-customer aggregates.

Question 19Get started with Dynamics 365 Customer Insights - Data

Two business units disagree about which email address should represent a customer. The administrator must ensure a predictable, documented outcome across all profiles. What is the most appropriate solution?

  1. Ask users to manually correct email addresses in the source systems after each refresh
  2. Exclude email from all source systems to avoid conflicts
  3. Define field-level precedence in the merge policy so the chosen source consistently wins Correct answer.
  4. Turn off matching so each source record keeps its own email address

Explanation

Merge policies establish deterministic field-level precedence, so the same rule resolves conflicts consistently for every profile. Manual correction, data removal, or disabling matching either fails to scale or defeats unification.

Question 20Get started with Dynamics 365 Customer Insights - Data

An administrator is asked to explain why a newly added source does not appear in segment conditions immediately after ingestion completes. Which explanation is most accurate?

  1. Measures must be removed and rebuilt before source attributes become available
  2. Segments can only reference sources that were added during the initial environment setup
  3. Unification must run so the new source data is matched and merged into unified profiles before segments can use it Correct answer.
  4. Export destinations must be deleted and recreated before any new attributes appear

Explanation

Segment conditions operate on unified profiles, so newly ingested source data becomes usable only after the unification process matches and merges it. There is no setup-time restriction on sources, and exports or measures do not gate attribute availability.

Question 21Ingest data into Dynamics 365 Customer Insights - Data

A data engineer is creating a new data source in Dynamics 365 Customer Insights - Data by uploading a CSV file. Which requirement must the file meet before the system will accept it for ingestion?

  1. The file must contain a header row with unique column names. Correct answer.
  2. The file must be compressed as a ZIP archive.
  3. The file must contain no more than one thousand rows.
  4. The file must be encoded in UTF-16 only.

Explanation

When you upload a CSV as a data source, Customer Insights - Data requires a header row whose column names are unique so each field can be mapped to an entity attribute. The file is commonly UTF-8 and can be large, so compression and row limits are not mandatory conditions.

Question 22Ingest data into Dynamics 365 Customer Insights - Data

Which connector type should an administrator choose to bring in customer records that currently live in an Azure SQL database without exporting them to files first?

  1. A manual CSV upload
  2. A Microsoft Dataverse source
  3. A Common Data Model folder
  4. A Power Query data source Correct answer.

Explanation

Power Query data sources in Customer Insights - Data use built-in connectors, including Azure SQL, to read data directly from the source system. Manual CSV upload and Common Data Model folders both require exported files rather than a live connection.

Question 23Ingest data into Dynamics 365 Customer Insights - Data

An organization wants to ingest data from a Common Data Model folder stored in Azure Data Lake Storage. What must exist before the source can be configured successfully?

  1. A provisioned Dataverse environment
  2. A published Power BI dataset
  3. A registered app with a client secret in Microsoft Entra ID
  4. A model.json manifest describing the entities Correct answer.

Explanation

A Common Data Model folder source relies on a model.json manifest that describes the entities and their attribute mappings in the folder. Customer Insights - Data reads that manifest to understand the schema before ingesting the data.

Question 24Ingest data into Dynamics 365 Customer Insights - Data

During data source configuration, the system flags several columns that could not be automatically typed. What is the recommended action to ensure correct ingestion?

  1. Delete the flagged columns from the source file.
  2. Convert the entire source to a single text column.
  3. Re-upload the file until automatic detection succeeds.
  4. Review and manually set the correct data type for each column. Correct answer.

Explanation

Customer Insights - Data lets you review and adjust the inferred data types for each column during source setup. Manually correcting the type ensures values are ingested and unified correctly rather than being dropped or misinterpreted.

Question 25Ingest data into Dynamics 365 Customer Insights - Data

What is the primary purpose of the data unification (map, match, merge) process after ingestion?

  1. To enforce row-level security on the source entities
  2. To combine records from multiple sources into unified customer profiles Correct answer.
  3. To schedule recurring refreshes of the source systems
  4. To compress the ingested tables for storage savings

Explanation

Unification maps source fields to a common schema, matches records that represent the same customer, and merges them into a single unified profile. This produces consolidated customer entities used for measures, segments, and insights.

Question 26Ingest data into Dynamics 365 Customer Insights - Data

In the unification map step, a source table has a column named 'EmailAddress' that should feed the unified 'Email' attribute. What should the engineer do?

  1. Map the source column to the standard Email attribute. Correct answer.
  2. Ignore the column and rely on automatic matching.
  3. Create a new custom attribute named EmailAddress.
  4. Rename the column in the source database first.

Explanation

The map step lets you associate each source column with the corresponding unified attribute, so EmailAddress is mapped to Email. Mapping aligns schemas across sources before matching and merging occur.

Question 27Ingest data into Dynamics 365 Customer Insights - Data

Which matching approach uses exact equality of attribute values to identify duplicate customer records?

  1. Exact matching on a chosen attribute such as email Correct answer.
  2. Machine learning-based scoring
  3. Fuzzy matching on name and address
  4. Rule-based exclusion matching

Explanation

Exact matching identifies records as duplicates only when the selected attribute values are identical, such as the same email address. Fuzzy matching, by contrast, tolerates variations and uses similarity scoring.

Question 28Ingest data into Dynamics 365 Customer Insights - Data

A company wants records to be considered duplicates when names are spelled slightly differently, such as 'Jon' and 'John'. Which matching configuration supports this?

  1. Exclusion rule on the name field
  2. Fuzzy match with an appropriate similarity threshold Correct answer.
  3. Merge policy set to 'keep first'
  4. Exact match on the full name

Explanation

Fuzzy matching compares values using similarity scoring and applies a threshold so near-variants like 'Jon' and 'John' can be treated as the same customer. Exact matching would require identical strings and miss these cases.

Question 29Ingest data into Dynamics 365 Customer Insights - Data

When merging matched records, an engineer needs the most recent value for a phone number to appear on the unified profile. Which merge option accomplishes this?

  1. First available
  2. Most frequent
  3. Highest value
  4. Most recent Correct answer.

Explanation

The merge step offers options such as most recent, most frequent, and first available for each attribute. Choosing 'most recent' selects the value from the record with the latest timestamp for that attribute.

Question 30Ingest data into Dynamics 365 Customer Insights - Data

Which statement correctly describes how data sources are refreshed in Customer Insights - Data?

  1. Refreshes occur automatically every hour with no configuration.
  2. Refreshes are disabled once unification has run.
  3. A refresh schedule can be configured, and refreshes can also be triggered on demand. Correct answer.
  4. Sources refresh only when an administrator manually re-uploads every file.

Explanation

Customer Insights - Data lets you define a refresh schedule for data sources and also run refreshes on demand. This keeps unified profiles and downstream measures current with source changes.

Question 31Ingest data into Dynamics 365 Customer Insights - Data

An engineer is preparing source data for ingestion and wants to minimize failures during refresh. Which practice best supports reliable ingestion?

  1. Include duplicate column names to preserve all fields
  2. Keep a consistent schema with stable column names and types Correct answer.
  3. Store dates in multiple inconsistent formats
  4. Change column names on each export

Explanation

A stable schema with consistent column names and data types allows the configured mappings to remain valid across refreshes. Frequent schema changes or inconsistent formats cause type and mapping errors during ingestion.

Question 32Ingest data into Dynamics 365 Customer Insights - Data

What does the 'ingestion' stage of a data source in Customer Insights - Data actually do?

  1. Publishes measures to Power BI dashboards
  2. Applies segmentation rules to customer profiles
  3. Deletes source records after processing
  4. Loads the source records into the platform's staging storage Correct answer.

Explanation

Ingestion loads the records from the configured source into the platform so they can be mapped and unified. Segmentation, measures, and publishing happen in later stages of the pipeline.

Question 33Ingest data into Dynamics 365 Customer Insights - Data

An organization needs to ingest data from Microsoft Dataverse tables into Customer Insights - Data. Which source type should be selected?

  1. Azure Blob Storage
  2. Common Data Model folder
  3. Power Query with the Dataverse connector Correct answer.
  4. Manual CSV upload

Explanation

The Power Query data source includes a Dataverse connector that reads tables directly from the environment. This avoids exporting data to files and keeps the source connected for scheduled refreshes.

Question 34Ingest data into Dynamics 365 Customer Insights - Data

Which attribute is typically recommended as the primary key or customer identifier for matching in unification?

  1. A stable unique identifier such as a customer ID or email Correct answer.
  2. The source file name
  3. A randomly generated row number
  4. The record's ingestion timestamp

Explanation

Matching works best with a stable, unique attribute that consistently identifies a customer across sources, such as a customer ID or email address. Volatile or non-unique fields produce unreliable matches.

Question 35Ingest data into Dynamics 365 Customer Insights - Data

After unification, an engineer notices that some profiles contain conflicting values from two sources. What determines which value is shown on the unified profile?

  1. The size of each source file
  2. The number of columns in each source
  3. The merge policy configured for each attribute Correct answer.
  4. The order in which sources were created

Explanation

Merge policies, such as most recent, most frequent, or first available, decide which source value survives for each attribute. Source creation order and file characteristics do not control the merged output.

Question 36Ingest data into Dynamics 365 Customer Insights - Data

Which statement about the order of operations in Customer Insights - Data is correct?

  1. Data must be ingested and unified before measures and segments use the profiles. Correct answer.
  2. Measures are calculated during the ingestion stage.
  3. Segments can be created before any data source is configured.
  4. Unification runs before data is ingested from sources.

Explanation

The pipeline ingests source data, maps and unifies it into customer profiles, and then measures and segments operate on those unified profiles. Downstream artifacts depend on completed ingestion and unification.

Question 37Ingest data into Dynamics 365 Customer Insights - Data

A data engineer wants to validate that a newly configured source ingested the expected number of records. Where should they check?

  1. The measure definitions page
  2. The source's status and record counts shown after a refresh Correct answer.
  3. The environment's audit log for sign-ins
  4. The segment membership list

Explanation

After a refresh, the data source page shows status and record counts that confirm how many rows were ingested. This lets engineers verify the source loaded as expected before relying on downstream unification.

Question 38Ingest data into Dynamics 365 Customer Insights - Data

What is a key benefit of using a Power Query data source instead of manual CSV uploads for recurring ingestion?

  1. It eliminates the need for data unification.
  2. It guarantees that all records match exactly.
  3. It removes the need to map columns.
  4. It supports scheduled refreshes that re-read the source automatically. Correct answer.

Explanation

Power Query sources stay connected to the underlying system, so scheduled refreshes can re-read current data without manual exports. Unification, matching, and mapping are still required regardless of source type.

Question 39Ingest data into Dynamics 365 Customer Insights - Data

During unification, an engineer defines a match rule using email plus last name to reduce false positives. What is the effect of combining attributes in a match rule?

  1. Records match if any single attribute matches.
  2. The rule disables fuzzy matching entirely.
  3. Records must satisfy the combined criteria to be considered a match. Correct answer.
  4. The rule merges all records into one profile.

Explanation

Combining attributes in a match rule requires records to satisfy the combined criteria before they are treated as duplicates. Adding attributes like last name alongside email narrows matches and reduces incorrect pairings.

Question 40Ingest data into Dynamics 365 Customer Insights - Data

Which data source type is most appropriate when an organization already exports its data nightly into Azure Data Lake Storage in Common Data Model format?

  1. Manual CSV upload
  2. Power Query with an OData connector
  3. Microsoft Dataverse
  4. Common Data Model folder Correct answer.

Explanation

A Common Data Model folder source reads CDM-formatted files and their model.json manifest directly from storage. Since the organization already produces CDM files nightly, this source type aligns with the existing export.

Question 41Ingest data into Dynamics 365 Customer Insights - Data

An engineer maps a source 'SignupDate' column to a date attribute, but the source stores dates as text in varying formats. What is the most reliable approach?

  1. Standardize the date format and set the attribute type to Date during mapping. Correct answer.
  2. Leave the column unmapped and ignore it.
  3. Map the column to the customer name attribute.
  4. Store the column as a numeric type.

Explanation

Standardizing the date format and explicitly setting the attribute to a Date type ensures values parse correctly during ingestion. Inconsistent text formats otherwise cause type errors or incorrect values in unified profiles.

Question 42Ingest data into Dynamics 365 Customer Insights - Data

What happens to source records that fail to match any other record during unification?

  1. They are retained as their own unified profiles. Correct answer.
  2. They are moved to a quarantine folder permanently.
  3. They are deleted from the unified entity.
  4. They are merged into a random existing profile.

Explanation

Records that do not match another record still become individual unified profiles, preserving the customer. They are not discarded, because unmatched customers remain valid profiles for measures and segments.

Question 43Ingest data into Dynamics 365 Customer Insights - Data

Which capability allows an administrator to control how often a Power Query source pulls fresh data?

  1. The column data type settings
  2. The merge policy for each attribute
  3. The refresh schedule configured for the data source Correct answer.
  4. The match rule threshold

Explanation

The refresh schedule defines when the source re-reads data from the connected system. Merge policies, match rules, and data types affect unification outcomes rather than refresh timing.

Question 44Ingest data into Dynamics 365 Customer Insights - Data

An organization ingests the same customer from a CRM and a billing system. Which sequence correctly reflects how Customer Insights - Data produces one unified profile?

  1. Match, then ingest, then map
  2. Merge, then match, then map
  3. Map, then match, then merge Correct answer.
  4. Ingest, then segment, then merge

Explanation

Unification proceeds by mapping source columns to unified attributes, matching records that represent the same customer, and merging the matched records into one profile. This order ensures alignment before duplicate detection and consolidation.

Question 45Ingest data into Dynamics 365 Customer Insights - Data

Which statement best describes how the map step handles two sources that use different column names for the same concept, such as 'Surname' and 'LastName'?

  1. Each column becomes a separate unified entity.
  2. One column must be deleted to avoid conflicts.
  3. The columns are automatically merged without mapping.
  4. Both columns are mapped to the same unified attribute. Correct answer.

Explanation

The map step lets both source columns be associated with the same unified attribute, aligning different names for the same concept. This consistency is what allows matching and merging to compare equivalent fields across sources.

Question 46Ingest data into Dynamics 365 Customer Insights - Data

An administrator wants Customer Insights - Data to pull data from a Power Query source on a recurring schedule. Which setting controls when the source data is refreshed?

  1. The number of segments created from the data
  2. The unification match rule threshold
  3. The refresh schedule configured on the data source Correct answer.
  4. The environment's language and locale settings

Explanation

Each data source has its own refresh schedule that determines how often Customer Insights - Data pulls fresh data from the underlying connection. Administrators can set the frequency and timing so recurring ingestion stays current without manual uploads. Match rules, segments, and locale settings do not govern when source data is retrieved.

Question 47Ingest data into Dynamics 365 Customer Insights - Data

Which data source type should an administrator choose to ingest data that is already organized in Microsoft Dataverse tables within the same environment?

  1. A CSV file upload
  2. A Power Query connector to a website
  3. A manual Excel attachment
  4. A Microsoft Dataverse source Correct answer.

Explanation

Customer Insights - Data provides a native Microsoft Dataverse connector that reads tables directly from the connected environment. This avoids exporting data to files and re-uploading it. File-based and web connectors are unnecessary when the data already lives in Dataverse.

Question 48Ingest data into Dynamics 365 Customer Insights - Data

During ingestion, a source column stores phone numbers with inconsistent formats such as parentheses, dashes, and spaces. Which action best prepares this column for consistent use downstream?

  1. Delete the column and rely on another source
  2. Store the column as a numeric attribute
  3. Apply a transformation to standardize the format during ingestion Correct answer.
  4. Leave the values unchanged and hope unification resolves them

Explanation

Transformations applied during ingestion clean and standardize values before they reach unification and downstream analytics. Normalizing phone formats improves match quality and reporting consistency. Removing the column or leaving inconsistent values reduces data quality.

Question 49Ingest data into Dynamics 365 Customer Insights - Data

Which statement describes what the ingestion stage accomplishes for a configured data source?

  1. It merges duplicate records into unified profiles
  2. It defines which attributes appear on the customer card
  3. It creates measures and segments for reporting
  4. It loads source records into the Customer Insights - Data storage Correct answer.

Explanation

Ingestion is the stage that reads records from the connected source and brings them into Customer Insights - Data storage. Unification, mapping, and reporting happen in later stages. Understanding this boundary helps engineers troubleshoot where problems originate.

Question 50Ingest data into Dynamics 365 Customer Insights - Data

A data engineer wants to reduce ingestion failures caused by malformed rows in a recurring Power Query source. Which approach is most effective?

  1. Add transformation steps that filter or correct invalid rows before loading Correct answer.
  2. Increase the refresh frequency to overwrite bad rows
  3. Disable the refresh schedule entirely
  4. Create additional segments to isolate the bad rows

Explanation

Applying transformation steps in the Power Query source lets the engineer filter out or repair malformed rows before they reach Customer Insights - Data. This prevents recurring failures on each refresh. Refresh frequency, disabled schedules, and segments do not correct the underlying data quality issues.