Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (2023)

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APPLIES TO: Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (1)Azure Data Factory Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (2)Azure Synapse Analytics

This article outlines how to use a copy activity in Azure Data Factory or Synapse pipelines to copy data from and to Dynamics 365 (Microsoft Dataverse) or Dynamics CRM, and use a data flow to transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM. To learn more, read the Azure Data Factory and the Azure Synapse Analytics introduction articles.

Supported capabilities

This connector is supported for the following activities:

Supported capabilitiesIR
Copy activity (source/sink)① ②
Mapping data flow (source/sink)
Lookup activity① ②

① Azure integration runtime ② Self-hosted integration runtime

For a list of data stores that a copy activity supports as sources and sinks, see the Supported data stores table.

Note

Effective November 2020, Common Data Service has been renamed to Microsoft Dataverse. This article is updated to reflect the latest terminology.

This Dynamics connector supports Dynamics versions 7 through 9 for both online and on-premises. More specifically:

  • Version 7 maps to Dynamics CRM 2015.
  • Version 8 maps to Dynamics CRM 2016 and the early version of Dynamics 365.
  • Version 9 maps to the later version of Dynamics 365.

Refer to the following table of supported authentication types and configurations for Dynamics versions and products.

Dynamics versionsAuthentication typesLinked service samples
Dataverse

Dynamics 365 online

Dynamics CRM online

Azure Active Directory (Azure AD) service principal

Office 365

User-assigned managed identity

Dynamics online and Azure AD service-principal or Office 365 authentication
Dynamics 365 on-premises with internet-facing deployment (IFD)

Dynamics CRM 2016 on-premises with IFD

Dynamics CRM 2015 on-premises with IFD

IFDDynamics on-premises with IFD and IFD authentication

Note

With the deprecation of regional Discovery Service, the service has upgraded to leverage global Discovery Service while using Office 365 Authentication.

Important

If your tenant and user is configured in Azure Active Directory for conditional access and/or Multi-Factor Authentication is required, you will not be able to use Office 365 Authentication type. For those situations, you must use an Azure Active Directory (Azure AD) service principal authentication.

For Dynamics 365 specifically, the following application types are supported:

(Video) 2. Dynamic CRM / ADF -Data set | Azure Data Factory Dataset for Dynamics

  • Dynamics 365 for Sales
  • Dynamics 365 for Customer Service
  • Dynamics 365 for Field Service
  • Dynamics 365 for Project Service Automation
  • Dynamics 365 for Marketing

This connector doesn't support other application types like Finance, Operations, and Talent.

Tip

To copy data from Dynamics 365 Finance and Operations, you can use the Dynamics AX connector.

This Dynamics connector is built on top of Dynamics XRM tooling.

Prerequisites

To use this connector with Azure AD service-principal authentication, you must set up server-to-server (S2S) authentication in Dataverse or Dynamics. First register the application user (Service Principal) in Azure Active Directory. You can find out how to do this here. During application registration you will need to create that user in Dataverse or Dynamics and grant permissions. Those permissions can either be granted directly or indirectly by adding the application user to a team which has been granted permissions in Dataverse or Dynamics. You can find more information on how to set up an application user to authenticate with Dataverse here.

Get started

To perform the Copy activity with a pipeline, you can use one of the following tools or SDKs:

  • The Copy Data tool
  • The Azure portal
  • The .NET SDK
  • The Python SDK
  • Azure PowerShell
  • The REST API
  • The Azure Resource Manager template

Create a linked service to Dynamics 365 (Microsoft Dataverse) or Dynamics CRM using UI

Use the following steps to create a linked service to Dynamics 365 in the Azure portal UI.

  1. Browse to the Manage tab in your Azure Data Factory or Synapse workspace and select Linked Services, then click New:

    • Azure Data Factory
    • Azure Synapse

    Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (3)

  2. Search for Dynamics or Dataverse and select the Dynamics 365 (Microsoft Dataverse) or Dynamics CRM connector.

    Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (4)

    Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (5)

  3. Configure the service details, test the connection, and create the new linked service.

    Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (6)

Connector configuration details

The following sections provide details about properties that are used to define entities specific to Dynamics.

Linked service properties

The following properties are supported for the Dynamics linked service.

Dynamics 365 and Dynamics CRM online

PropertyDescriptionRequired
typeThe type property must be set to "Dynamics", "DynamicsCrm", or "CommonDataServiceForApps".Yes
deploymentTypeThe deployment type of the Dynamics instance. The value must be "Online" for Dynamics online.Yes
serviceUriThe service URL of your Dynamics instance, the same one you access from browser. An example is "https://<organization-name>.crm[x].dynamics.com".Yes
authenticationTypeThe authentication type to connect to a Dynamics server. Valid values are "AADServicePrincipal", "Office365" and "ManagedIdentity".Yes
servicePrincipalIdThe client ID of the Azure AD application.Yes when authentication is "AADServicePrincipal"
servicePrincipalCredentialTypeThe credential type to use for service-principal authentication. Valid values are "ServicePrincipalKey" and "ServicePrincipalCert".Yes when authentication is "AADServicePrincipal"
servicePrincipalCredentialThe service-principal credential.

When you use "ServicePrincipalKey" as the credential type, servicePrincipalCredential can be a string that the service encrypts upon linked service deployment. Or it can be a reference to a secret in Azure Key Vault.

When you use "ServicePrincipalCert" as the credential, servicePrincipalCredential must be a reference to a certificate in Azure Key Vault, and ensure the certificate content type is PKCS #12.

Yes when authentication is "AADServicePrincipal"
usernameThe username to connect to Dynamics.Yes when authentication is "Office365"
passwordThe password for the user account you specified as the username. Mark this field with "SecureString" to store it securely, or reference a secret stored in Azure Key Vault.Yes when authentication is "Office365"
credentialsSpecify the user-assigned managed identity as the credential object.

Create one or multiple user-assigned managed identities, assign them to your data factory and create credentials for each user-assigned managed identity.

Yes when authentication is "ManagedIdentity"
connectViaThe integration runtime to be used to connect to the data store. If no value is specified, the property uses the default Azure integration runtime.No

Note

The Dynamics connector formerly used the optional organizationName property to identify your Dynamics CRM or Dynamics 365 online instance. While that property still works, we suggest you specify the new serviceUri property instead to gain better performance for instance discovery.

(Video) Azure Data Factory and Dynamics CRM Online

Example: Dynamics online using Azure AD service-principal and key authentication

{ "name": "DynamicsLinkedService", "properties": { "type": "Dynamics", "typeProperties": { "deploymentType": "Online", "serviceUri": "https://<organization-name>.crm[x].dynamics.com", "authenticationType": "AADServicePrincipal", "servicePrincipalId": "<service principal id>", "servicePrincipalCredentialType": "ServicePrincipalKey", "servicePrincipalCredential": "<service principal key>" }, "connectVia": { "referenceName": "<name of Integration Runtime>", "type": "IntegrationRuntimeReference" } } } 

Example: Dynamics online using Azure AD service-principal and certificate authentication

{ "name": "DynamicsLinkedService", "properties": { "type": "Dynamics", "typeProperties": { "deploymentType": "Online", "serviceUri": "https://<organization-name>.crm[x].dynamics.com", "authenticationType": "AADServicePrincipal", "servicePrincipalId": "<service principal id>", "servicePrincipalCredentialType": "ServicePrincipalCert", "servicePrincipalCredential": { "type": "AzureKeyVaultSecret", "store": { "referenceName": "<AKV reference>", "type": "LinkedServiceReference" }, "secretName": "<certificate name in AKV>" } }, "connectVia": { "referenceName": "<name of Integration Runtime>", "type": "IntegrationRuntimeReference" } } } 

Example: Dynamics online using Office 365 authentication

{ "name": "DynamicsLinkedService", "properties": { "type": "Dynamics", "typeProperties": { "deploymentType": "Online", "serviceUri": "https://<organization-name>.crm[x].dynamics.com", "authenticationType": "Office365", "username": "test@contoso.onmicrosoft.com", "password": { "type": "SecureString", "value": "<password>" } }, "connectVia": { "referenceName": "<name of Integration Runtime>", "type": "IntegrationRuntimeReference" } }}

Example: Dynamics online using user-assigned managed identity authentication

{ "name": "DynamicsLinkedService", "properties": { "type": "Dynamics", "typeProperties": { "deploymentType": "Online", "serviceUri": "https://<organization-name>.crm[x].dynamics.com", "authenticationType": "ManagedIdentity", "credential": { "referenceName": "credential1", "type": "CredentialReference" } }, "connectVia": { "referenceName": "<name of Integration Runtime>", "type": "IntegrationRuntimeReference" } }}

Dynamics 365 and Dynamics CRM on-premises with IFD

Additional properties that compare to Dynamics online are hostName and port.

PropertyDescriptionRequired
typeThe type property must be set to "Dynamics", "DynamicsCrm", or "CommonDataServiceForApps".Yes.
deploymentTypeThe deployment type of the Dynamics instance. The value must be "OnPremisesWithIfd" for Dynamics on-premises with IFD.Yes.
hostNameThe host name of the on-premises Dynamics server.Yes.
portThe port of the on-premises Dynamics server.No. The default value is 443.
organizationNameThe organization name of the Dynamics instance.Yes.
authenticationTypeThe authentication type to connect to the Dynamics server. Specify "Ifd" for Dynamics on-premises with IFD.Yes.
usernameThe username to connect to Dynamics.Yes.
passwordThe password for the user account you specified for the username. You can mark this field with "SecureString" to store it securely. Or you can store a password in Key Vault and let the copy activity pull from there when it does data copy. Learn more from Store credentials in Key Vault.Yes.
connectViaThe integration runtime to be used to connect to the data store. If no value is specified, the property uses the default Azure integration runtime.No

Example: Dynamics on-premises with IFD using IFD authentication

{ "name": "DynamicsLinkedService", "properties": { "type": "Dynamics", "description": "Dynamics on-premises with IFD linked service using IFD authentication", "typeProperties": { "deploymentType": "OnPremisesWithIFD", "hostName": "contosodynamicsserver.contoso.com", "port": 443, "organizationName": "admsDynamicsTest", "authenticationType": "Ifd", "username": "test@contoso.onmicrosoft.com", "password": { "type": "SecureString", "value": "<password>" } }, "connectVia": { "referenceName": "<name of Integration Runtime>", "type": "IntegrationRuntimeReference" } }}

Dataset properties

For a full list of sections and properties available for defining datasets, see the Datasets article. This section provides a list of properties supported by Dynamics dataset.

To copy data from and to Dynamics, the following properties are supported:

PropertyDescriptionRequired
typeThe type property of the dataset must be set to "DynamicsEntity", "DynamicsCrmEntity", or "CommonDataServiceForAppsEntity".Yes
entityNameThe logical name of the entity to retrieve.No for source if the activity source is specified as "query" and yes for sink

Example

{ "name": "DynamicsDataset", "properties": { "type": "DynamicsEntity", "schema": [], "typeProperties": { "entityName": "account" }, "linkedServiceName": { "referenceName": "<Dynamics linked service name>", "type": "linkedservicereference" } }}

Copy activity properties

For a full list of sections and properties available for defining activities, see the Pipelines article. This section provides a list of properties supported by Dynamics source and sink types.

Dynamics as a source type

To copy data from Dynamics, the copy activity source section supports the following properties:

PropertyDescriptionRequired
typeThe type property of the copy activity source must be set to "DynamicsSource", "DynamicsCrmSource", or "CommonDataServiceForAppsSource".Yes
queryFetchXML is a proprietary query language that is used in Dynamics online and on-premises. See the following example. To learn more, see Build queries with FetchXML.No if entityName in the dataset is specified

Note

The PK column will always be copied out even if the column projection you configure in the FetchXML query doesn't contain it.

Important

  • When you copy data from Dynamics, explicit column mapping from Dynamics to sink is optional. But we highly recommend the mapping to ensure a deterministic copy result.
  • When the service imports a schema in the authoring UI, it infers the schema. It does so by sampling the top rows from the Dynamics query result to initialize the source column list. In that case, columns with no values in the top rows are omitted. The same behavior also applies to data preview and copy executions if there is no explicit mapping. You can review and add more columns into the mapping, which are honored during copy runtime.

Example

"activities":[ { "name": "CopyFromDynamics", "type": "Copy", "inputs": [ { "referenceName": "<Dynamics input dataset>", "type": "DatasetReference" } ], "outputs": [ { "referenceName": "<output dataset>", "type": "DatasetReference" } ], "typeProperties": { "source": { "type": "DynamicsSource", "query": "<FetchXML Query>" }, "sink": { "type": "<sink type>" } } }]

Sample FetchXML query

<fetch> <entity name="account"> <attribute name="accountid" /> <attribute name="name" /> <attribute name="marketingonly" /> <attribute name="modifiedon" /> <order attribute="modifiedon" descending="false" /> <filter type="and"> <condition attribute ="modifiedon" operator="between"> <value>2017-03-10 18:40:00z</value> <value>2017-03-12 20:40:00z</value> </condition> </filter> </entity></fetch>

Dynamics as a sink type

To copy data to Dynamics, the copy activity sink section supports the following properties:

PropertyDescriptionRequired
typeThe type property of the copy activity sink must be set to "DynamicsSink", "DynamicsCrmSink", or "CommonDataServiceForAppsSink".Yes.
writeBehaviorThe write behavior of the operation. The value must be "Upsert".Yes
alternateKeyNameThe alternate key name defined on your entity to do an upsert.No.
writeBatchSizeThe row count of data written to Dynamics in each batch.No. The default value is 10.
ignoreNullValuesWhether to ignore null values from input data other than key fields during a write operation.

Valid values are TRUE and FALSE:

  • TRUE: Leave the data in the destination object unchanged when you do an upsert or update operation. Insert a defined default value when you do an insert operation.
  • FALSE: Update the data in the destination object to a null value when you do an upsert or update operation. Insert a null value when you do an insert operation.
No. The default value is FALSE.
maxConcurrentConnectionsThe upper limit of concurrent connections established to the data store during the activity run. Specify a value only when you want to limit concurrent connections.No

Note

The default value for both the sink writeBatchSize and the copy activity parallelCopies for the Dynamics sink is 10. Therefore, 100 records are concurrently submitted by default to Dynamics.

For Dynamics 365 online, there's a limit of 52 concurrent batch calls per organization. If that limit is exceeded, a "Server Busy" exception is thrown before the first request is ever run. Keep writeBatchSize at 10 or less to avoid such throttling of concurrent calls.

The optimal combination of writeBatchSize and parallelCopies depends on the schema of your entity. Schema elements include the number of columns, row size, and number of plug-ins, workflows, or workflow activities hooked up to those calls. The default setting of writeBatchSize (10) × parallelCopies (10) is the recommendation according to the Dynamics service. This value works for most Dynamics entities, although it might not give the best performance. You can tune the performance by adjusting the combination in your copy activity settings.

Example

"activities":[ { "name": "CopyToDynamics", "type": "Copy", "inputs": [ { "referenceName": "<input dataset>", "type": "DatasetReference" } ], "outputs": [ { "referenceName": "<Dynamics output dataset>", "type": "DatasetReference" } ], "typeProperties": { "source": { "type": "<source type>" }, "sink": { "type": "DynamicsSink", "writeBehavior": "Upsert", "writeBatchSize": 10, "ignoreNullValues": true } } }]

Retrieving data from views

To retrieve data from Dynamics views, you need to get the saved query of the view, and use the query to get the data.

(Video) Use Azure Data Factory to copy and transform data

There are two entities which store different types of view: "saved query" stores system view and "user query" stores user view. To get the information of the views, refer to the following FetchXML query and replace the "TARGETENTITY" with savedquery or userquery. Each entity type has more available attributes that you can add to the query based on your need. Learn more about savedquery entity and userquery entity.

<fetch top="5000" > <entity name="<TARGETENTITY>"> <attribute name="name" /> <attribute name="fetchxml" /> <attribute name="returnedtypecode" /> <attribute name="querytype" /> </entity></fetch>

You can also add filters to filter the views. For example, add the following filter to get a view named "My Active Accounts" in account entity.

<filter type="and" > <condition attribute="returnedtypecode" operator="eq" value="1" /> <condition attribute="name" operator="eq" value="My Active Accounts" /></filter>

Data type mapping for Dynamics

When you copy data from Dynamics, the following table shows mappings from Dynamics data types to interim data types within the service. To learn how a copy activity maps to a source schema and a data type maps to a sink, see Schema and data type mappings.

Configure the corresponding interim data type in a dataset structure that is based on your source Dynamics data type by using the following mapping table:

Dynamics data typeService interim data typeSupported as sourceSupported as sink
AttributeTypeCode.BigIntLong
AttributeTypeCode.BooleanBoolean
AttributeType.CustomerGUID✓ (See guidance)
AttributeType.DateTimeDatetime
AttributeType.DecimalDecimal
AttributeType.DoubleDouble
AttributeType.EntityNameString
AttributeType.IntegerInt32
AttributeType.LookupGUID✓ (See guidance)
AttributeType.ManagedPropertyBoolean
AttributeType.MemoString
AttributeType.MoneyDecimal
AttributeType.OwnerGUID✓ (See guidance)
AttributeType.PicklistInt32
AttributeType.UniqueidentifierGUID
AttributeType.StringString
AttributeType.StateInt32
AttributeType.StatusInt32

Note

The Dynamics data types AttributeType.CalendarRules, AttributeType.MultiSelectPicklist, and AttributeType.PartyList aren't supported.

Writing data to a lookup field

To write data into a lookup field with multiple targets like Customer and Owner, follow this guidance and example:

  1. Make your source contains both the field value and the corresponding target entity name.

    • If all records map to the same target entity, ensure one of the following conditions:
      • Your source data has a column that stores the target entity name.
      • You've added an additional column in the copy activity source to define the target entity.
    • If different records map to different target entities, make sure your source data has a column that stores the corresponding target entity name.
  2. Map both the value and entity-reference columns from source to sink. The entity-reference column must be mapped to a virtual column with the special naming pattern {lookup_field_name}@EntityReference. The column doesn't actually exist in Dynamics. It's used to indicate this column is the metadata column of the given multitarget lookup field.

For example, assume the source has these two columns:

  • CustomerField column of type GUID, which is the primary key value of the target entity in Dynamics.
  • Target column of type String, which is the logical name of the target entity.

Also assume you want to copy such data to the sink Dynamics entity field CustomerField of type Customer.

In copy-activity column mapping, map the two columns as follows:

  • CustomerField to CustomerField. This mapping is the normal field mapping.
  • Target to CustomerField@EntityReference. The sink column is a virtual column representing the entity reference. Input such field names in a mapping, as they won't show up by importing schemas.

Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (7)

If all of your source records map to the same target entity and your source data doesn't contain the target entity name, here is a shortcut: in the copy activity source, add an additional column. Name the new column by using the pattern {lookup_field_name}@EntityReference, set the value to the target entity name, then proceed with column mapping as usual. If your source and sink column names are identical, you can also skip explicit column mapping because copy activity by default maps columns by name.

Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (8)

Writing data to a lookup field via alternative keys

To write data into a lookup field using alternate key columns, follow this guidance and example:

  1. Ensure your source contains all the lookup key columns.

  2. The alternate key columns must be mapped to the column with the special naming pattern {lookup_field_name}@{alternate_key_column_name}. The column doesn't exist in Dynamics. It's used to indicate that this column is used to look up the record in the target entity.

    (Video) SQL to Dataverse Data Migration using Azure Data Factory | Power Apps

  3. Go to Mapping tab in the sink transformation of mapping data flows. Select the alternate key as output columns under the Lookup field. The value after indicates the key columns of this alternate key.

    Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (9)

  4. Once selected, the alternate key columns will automatically display in below.

    Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (10)

  5. Map your input columns on left with the output columns.

    Copy and transform data in Dynamics 365 (Microsoft Dataverse) or Dynamics CRM - Azure Data Factory & Azure Synapse (11)

Note

Currently this is only supported when you use inline mode in the sink transformation of mapping data flows.

Mapping data flow properties

When transforming data in mapping data flow, you can read from and write to tables in Dynamics. For more information, see the source transformation and sink transformation in mapping data flows. You can choose to use a Dynamics dataset or an inline dataset as source and sink type.

Source transformation

The below table lists the properties supported by Dynamics. You can edit these properties in the Source options tab.

NameDescriptionRequiredAllowed valuesData flow script property
Entity nameThe logical name of the entity to retrieve.Yes when use inline dataset-(for inline dataset only)
entity
QueryFetchXML is a proprietary query language that is used in Dynamics online and on-premises. See the following example. To learn more, see Build queries with FetchXML.NoStringquery

Note

If you select Query as input type, the column type from tables can not be retrieved. It will be treated as string by default.

Dynamics source script example

When you use Dynamics dataset as source type, the associated data flow script is:

source(allowSchemaDrift: true,validateSchema: false,query: '<fetch mapping='logical' count='3 paging-cookie=''><entity name='new_dataflow_crud_test'><attribute name='new_name'/><attribute name='new_releasedate'/></entity></fetch>') ~> DynamicsSource

If you use inline dataset, the associated data flow script is:

source(allowSchemaDrift: true,validateSchema: false,store: 'dynamics',format: 'dynamicsformat',entity: 'Entity1',query: '<fetch mapping='logical' count='3 paging-cookie=''><entity name='new_dataflow_crud_test'><attribute name='new_name'/><attribute name='new_releasedate'/></entity></fetch>') ~> DynamicsSource

Sink transformation

The below table lists the properties supported by Dynamics sink. You can edit these properties in the Sink options tab.

NameDescriptionRequiredAllowed valuesData flow script property
Alternate key nameThe alternate key name defined on your entity to do an update, upsert or delete.No-alternateKeyName
Update methodSpecify what operations are allowed on your database destination. The default is to only allow inserts.
To update, upsert, or delete rows, an Alter row transformation is required to tag rows for those actions.
Yestrue or falseinsertable
updateable
upsertable
deletable
Entity nameThe logical name of the entity to write.Yes when use inline dataset-(for inline dataset only)
entity

Dynamics sink script example

When you use Dynamics dataset as sink type, the associated data flow script is:

IncomingStream sink(allowSchemaDrift: true, validateSchema: false, deletable:true, insertable:true, updateable:true, upsertable:true, skipDuplicateMapInputs: true, skipDuplicateMapOutputs: true) ~> DynamicsSink

If you use inline dataset, the associated data flow script is:

(Video) ADF - 2 (Integrating Microsoft Dynamic CRM to External System (SQL))

IncomingStream sink(allowSchemaDrift: true, validateSchema: false, store: 'dynamics', format: 'dynamicsformat', entity: 'Entity1', deletable: true, insertable: true, updateable: true, upsertable: true, skipDuplicateMapInputs: true, skipDuplicateMapOutputs: true) ~> DynamicsSink

Lookup activity properties

To learn details about the properties, see Lookup activity.

Next steps

For a list of supported data stores the copy activity as sources and sinks, see Supported data stores.

FAQs

Which of the following are valid options for transforming data within Azure data Factory? ›

Transform natively in Azure Data Factory and Azure Synapse Analytics with data flows
  • Mapping data flows. ...
  • Data wrangling. ...
  • HDInsight Hive activity. ...
  • HDInsight Pig activity. ...
  • HDInsight MapReduce activity. ...
  • HDInsight Streaming activity. ...
  • HDInsight Spark activity. ...
  • ML Studio (classic) activities.
Sep 23, 2022

What is the difference between Dataverse and Dynamics 365? ›

In short, Dataverse is a ready-to-use server that offers a security layer, a business layer, a data access layer and so on. Dynamics CRM solutions store their data on a Dynamics server, the business logic is implemented via plugins on Dataverse.

What is the difference between Azure data Factory and Azure Synapse analytics? ›

The main difference between the two services is that Synapse Analytics is an analytics service, and Data Factory is a hybrid data integration service that simplifies the ETL at scale.

Which 3 types of activities can you run in Microsoft Azure data Factory? ›

Data Factory supports three types of activities: data movement activities, data transformation activities, and control activities.

Can I use Dataverse as a database? ›

You can create a database and build apps by using Dataverse as a data store. You can either create your own custom tables or use the predefined tables. To create a database, you first need to either create an environment, or be assigned to an existing environment as an Environment Admin.

Why use Dataverse instead of SQL? ›

The key difference of Dataverse is that it is a relational database just like Microsoft SQL compared with the other options. This will allow you to form relationships and lookups to other tables of data. The downside of this option is that it will require premium licenses which can be quite costly.

What database does Microsoft Dataverse use? ›

Although Dataverse's main database is Azure SQL and Dataverse is referred to as a “database” in many places even within Microsoft space, it is much more than a database. Dataverse comes with a rich set of features that are usually common to any type of system/application especially in the enterprise space.

What are the limitations of Azure synapse database? ›

Limit is 8000 for char data types, 4000 for nvarchar, or 2 GB for MAX data types. The number of bytes per row is calculated in the same manner as it is for SQL Server with page compression. Like SQL Server, row-overflow storage is supported, which enables variable length columns to be pushed off-row.

Is Azure data Factory A ETL tool? ›

With Azure Data Factory, it's fast and easy to build code-free or code-centric ETL and ELT processes.

When should I use Databricks vs Azure data Factory? ›

The last and most significant difference between the two tools is that ADF is generally used for data movement, ETL process, and data orchestration whereas; Databricks helps in data streaming and data collaboration in real-time.

Does Dynamics 365 use Dataverse? ›

Dynamics 365 and Dataverse

Dynamics 365 applications—such as Dynamics 365 Sales, Dynamics 365 Customer Service, or Dynamics 365 Talent—also use Dataverse to store and secure the data they use.

Is Dynamics 365 being discontinued? ›

The Microsoft Dynamics 365 (Preview) app for Windows was deprecated on June 20, 2022. The app is no longer supported.

What is Azure Synapse link for Dataverse? ›

Azure Synapse Link for Microsoft Dataverse was formerly known as Export to data lake. The service was renamed effective May 2021 and will continue to export data to Azure Data Lake as well as Azure Synapse Analytics.

What are the limitations of Azure Data Factory? ›

Version 2
ResourceDefault limitMaximum limit
Total number of entities, such as pipelines, data sets, triggers, linked services, Private Endpoints, and integration runtimes, within a data factory5,000Contact support.
Total CPU cores for Azure-SSIS Integration Runtimes under one subscription64Contact support.
29 more rows

What are the two types of data movement to Microsoft Azure? ›

The data movement can be of the following types: Offline transfer using shippable devices - Use physical shippable devices when you want to do offline one-time bulk data transfer.

What is copy data in Azure Data Factory? ›

In Azure Data Factory and Synapse pipelines, you can use the Copy activity to copy data among data stores located on-premises and in the cloud. After you copy the data, you can use other activities to further transform and analyze it.

What are the two types of data transformation? ›

During the transformation process, an analyst or engineer will determine the data structure. The most common types of data transformation are: Constructive: The data transformation process adds, copies, or replicates data. Destructive: The system deletes fields or records.

What are the three most common transformations in ETL processes? ›

ETL transformation types

Basic transformations: Cleaning: Mapping NULL to 0 or "Male" to "M" and "Female" to "F," date format consistency, etc. Deduplication: Identifying and removing duplicate records. Format revision: Character set conversion, unit of measurement conversion, date/time conversion, etc.

What are the 4 basic transformation? ›

There are four major types of transformations namely:
  • Rotation.
  • Translation.
  • Dilation.
  • Reflection.

Is Dataverse same as SQL? ›

Dataverse data is stored in a combination of Azure SQL and Azure Blob storage. Azure SQL Database is a relational database service built for the cloud.

Is Dataverse the same as Azure SQL? ›

Dataverse stores table data in Azure SQL, Azure SQL Storage, Cosmos DB, Azure Data Lake, and Cognitive Search. For instance, Cosmos DB is used to store audit logs. In addition, all these data storage types are encrypted at rest using a Microsoft-managed encryption key.

Is Dataverse an Azure SQL database? ›

Azure Synapse Link for Microsoft Dataverse was formerly known as Export to data lake. The service was renamed effective May 2021 and will continue to export data to Azure Data Lake as well as Azure Synapse Analytics.

Is Dataverse a CRM? ›

Microsoft Dataverse originates from Microsoft Dynamics CRM. As Microsoft's CRM/xRM platform evolved into Power Platform concepts like editing existing data models, creating new data models and managing security for your application was transformed into the Common Data Service (CDS).

Is Microsoft Dataverse a data lake? ›

Azure Synapse Link for Dataverse was formerly known as Export to data lake. The service was renamed effective May 2021 and will continue to export data to Azure Data Lake as well as Azure Synapse Analytics.

Is Dataverse a cloud database? ›

In fact, and to simplify Microsoft Dataverse is a database hosted in Microsoft Dynamics 365. It provides a cloud-based storage for your data if you are using Microsoft Dynamics 365. It has standard and custom tables that let you store the data - and is organized in columns, tables, rows.

How many records can Dataverse handle? ›

With Dataverse for Teams, there is a limit in storage capacity (1 million rows or 2 GB). If you think you will need to manage more data than this, then you should consider Dataverse.

What is the difference between Dataverse and data lake? ›

Having the data stored in Azure Data Lake Storage increases the writing speed to a destination. Compared to Dataverse (which might have many rules to check at the time of data storage), Azure Data Lake Storage is faster for read/write transactions on a large amount of data.

Is Dataverse better than SharePoint list? ›

If you're a small organisation who is just starting out with Power Apps and don't really expect to have a lot of data, then SharePoint Lists might be a good starting point. For bigger projects, solutions and applications you expect to scale, then Dataverse would be the better route to take.

Is Azure Synapse a ETL tool? ›

Azure Synapse and Snowflake are two commonly recommended ETL tools for businesses that need to process large amounts of data.

Is Azure Synapse A ETL? ›

Basically, Azure Synapse completes the whole data integration and ETL process and is much more than a normal data warehouse since it includes further stages of the process giving the users the possibility to also create reports and visualizations.

What database does Azure synapse use? ›

Azure Synapse SQL is a big data analytic service that enables you to query and analyze your data using the T-SQL language. You can use standard ANSI-compliant dialect of SQL language used on SQL Server and Azure SQL Database for data analysis.

Is Azure data/factory ETL or ELT? ›

With Azure Data Factory, it is fast and easy to build code-free or code-centric ETL and ELT processes.

What is the most popular ETL tool? ›

Informatica PowerCenter is one of the best ETL tools on the market. It has a wide range of connectors for cloud data warehouses and lakes, including AWS, Azure, Google Cloud, and SalesForce. Its low- and no-code tools are designed to save time and simplify workflows.

Is it worth to learn Azure Data factory? ›

Azure Data Factory is a good product when you design a good data engineering architecture. Azure Data Factory helps us on data movement, integration and transformation. We can automate the process on collecting data sources (e.g. file system) and move the data to destination (e.g Azure Synapse).

What is the difference between Databricks and synapse? ›

Azure Synapse vs Databricks: What is the Difference? Azure Synapse successfully integrates analytical services to bring enterprise data warehouse and big data analytics into a single platform. On the other hand, Databricks not only does big data analytics but also allows users to build complex ML products at scale.

Is Azure Data Factory similar to SSIS? ›

SQL Server Integration Service (SSIS) is an on-premises ETL technology intended for use in on-premises applications. Azure Data Factory is a data pipeline orchestrator based in the cloud. While both SSIS and Azure Data Factory are ETL tools, there are subtle differences between the two.

Does Azure Data Factory use Spark? ›

Azure Data Factory automatically creates an HDInsight cluster and runs the Spark program.

Is Microsoft Dataverse in Azure? ›

Microsoft Dataverse supports integration with Azure.

How do I connect Dynamics 365 to Dataverse? ›

Connecting to Microsoft Dataverse
  1. Register an Azure AD application.
  2. Add an application user to Dynamics.
  3. Data connector settings. Upgrading from previous versions.

Can you import Excel into Dataverse? ›

Select Data, to the right of Get Data select >, and then select Get data from Excel. Select the tables where you want to import data, and then select Next. On the Import data page, select Upload, and choose your file. Follow the prompts to upload your file.

What programming language is Dynamics 365? ›

As we mentioned, X++ is the main programming language of Dynamics AX, now rebranded as Dynamics 365 for Finance and Operations. This programming language powers all the items and elements that you can find within this Microsoft environment.

Why is Salesforce better than Dynamics 365? ›

Salesforce is generally more user-friendly in the UI department, and more customizable, but Microsoft Dynamics 365 is probably a bit easier to use for reporting. Then again, if you really want or need an on-premise deployment, a Microsoft Dynamics 365 plan is the only way to go—Salesforce is cloud-based, full-stop.

Is Dynamics 365 better than SAP? ›

Microsoft Dynamics 365 outshines SAP Business One as it comes equipped with several features which provide scalability, flexibility, and lower implementation and ownership costs, and significantly benefit both start-ups and the largest of enterprises.

Which of the following are included in data transformation? ›

Data transformation is crucial to data management processes that include data integration, data migration, data warehousing and data preparation. The process of data transformation can also be referred to as extract/transform/load (ETL).

Which of the following are data transformation techniques? ›

There are 6 basic data transformation techniques that you can use in your analysis project or data pipeline:
  • Data Smoothing.
  • Attribution Construction.
  • Data Generalization.
  • Data Aggregation.
  • Data Discretization.
  • Data Normalization.
Jun 13, 2022

What is source transformation in Azure Data Factory? ›

Workspace DB (Synapse workspaces only)

In Azure Synapse workspaces, an additional option is present in data flow source transformations called Workspace DB . This will allow you to directly pick a workspace database of any available type as your source data without requiring additional linked services or datasets.

What is select transformation in Azure Data Factory? ›

In a select transformation, users can specify fixed mappings, use patterns to do rule-based mapping, or enable auto mapping. Fixed and rule-based mappings can both be used within the same select transformation. If a column doesn't match one of the defined mappings, it will be dropped.

What are the 7 types of transformation process? ›

What Are The Types of Transformation Processes in Operations Management?
  • Material Processing. ...
  • Information Processing. ...
  • Customer Processing. ...
  • Possession Transformation. ...
  • Location Transformation. ...
  • Storage Transformation.
Dec 1, 2022

What are the 5 stages of transforming data into information? ›

To be effectively used in making decisions, data must go through a transformation process that involves six basic steps: 1) data collection, 2) data organization, 3) data processing, 4) data integration, 5) data reporting and finally, 6) data utilization.

Is Azure Data Factory A ETL tool? ›

With Azure Data Factory, it's fast and easy to build code-free or code-centric ETL and ELT processes.

Videos

1. How to ingest data from D365 to Azure Synapse Analytics?
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2. Integration of Blob Storage with D365 CRM Using Azure Data Factory - MVP Show ft. Venkata Subbarao
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3. Azure Data Factory - SQL Server to Dataverse
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4. Joe Griffin - Implementing Azure Data Solutions using Dynamics 365 & Microsoft Dataflex Pro
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5. BI/AI Architecture (Zero to Hero) for Dynamics 365 with Azure Synapse
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6. Extract Dynamics 365 for Finance and Operations to Azure Data Lake
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