>> You'll use data entities and data packages
when you manage data in Microsoft Dynamics
365 for Finance and Operations.
The activities that you'll use them for include:
Initial configuration of a new implementation
from an empty environment.
Data migration from legacy systems.
Copying a company configuration
within an existing environment.
And copying data across environments.
In this video, we'll share tips and tricks
for working with data entities and data packages.
Finance and Operations includes
a data management framework
that can be used in multiple ways.
Any data entity that a developer creates on
top of this framework can be used for data migration,
Microsoft Office integration,
and other types of integration.
Microsoft Dynamics 365 for Finance and
Operations includes over 2200 data entities.
You can view the list of standard data entities
in the Data Management Workspace.
Note that in a brand new environment,
this page might take a few seconds to
be loaded the first time that it's opened.
If there are any changes, for example,
the new data entity was
introduced in a recent deployment,
you can update the data entity list.
In the Data Management Workspace,
click "Framework Parameters."
Then, on the entity settings tab,
click "Refresh Entity List."
To move data into and out of Finance and Operations,
you must create an import/export data project
in the Data Management Workspace.
To import, you must create an import data project by
specifying the name of the data project, a description,
the name of the data entity,
and the source data format such as comma separate values,
also known as CSV,
Microsoft Excel or XML.
You then supply a sample file
to help Finance and Operations
build a mapping between your source file
and the internal staging table.
Automatic field mapping between
your source and staging is based on
the column header in your file
and the column name in the staging table.
If your source file has different column headings,
you can manually map them by using the View Map page.
To export, you must create an export data project by
specifying the name of the data project, a description,
the data entity, the target data formats such as CSV,
Excel, tab-separated values or package,
and the default refresh type.
If you want to export data based on specific criteria,
you can specify a filter.
Sometimes, you might want to
export just the changes to an entity.
In this case, you can set the default
refresh type field to incremental push only.
This option lets you export changes based
on Microsoft Sequel Server change tracking.
To use change tracking to export changes to an entity,
you must first configure change
tracking for your target data entity.
From the Data Management Workspace,
open the entities page,
then select your target data entity,
and turn on the appropriate type of change
tracking based on your requirements.
Note that Microsoft recently
introduced Data Entity Versioning.
Whenever Microsoft makes
any breaking changes to a data entity,
a new version of the entity is released.
For example, check out
the Customer and Customer V2 data entities in
Microsoft Dynamics 365 for
Finance and Operations with platform update nine.
Often, you might have to handle large volumes
of data as part of data management activities.
For example, you might have to migrate
your customer master data from
a legacy system to Finance and Operations.
For those data entities that
don't support set-based operations,
you can set up parallel data loading to
occur during the movement of data from staging to target.
To use parallel data loading,
you must first configure entity execution
parameters for your target data entity.
In the Data Management Workspace,
click "Framework Parameters."
Then on the Entity Settings tab,
click "Configure Entity Execution Parameters."
The current configuration indicates that
the customer groups entity uses the following algorithm.
If the record count is less than 50,
a single batch task is used to import all records.
If the record count is more than or
equal to 50 but less than 100,
two batch tasks are used to import records.
If the record count is more than 100,
four batch tasks are used to import records.
For all other data entities,
the following algorithm is used.
If the record count is less than 30,
a single batch task is used to load all records.
Otherwise, two batch tasks are used to load records.
Parallel data loading is
built on top of the batch framework.
Before you run an import job,
make sure that the import in batch option is set in
the project "Import options"
in the Data Management Workspace.
Data packages are a new concept that
was introduced in Finance and Operations.
A data package is a single-compressed file,
that is a zip file,
that contains a data project manifest and data files.
A data package lets
you import or export multiple data entities
in a defined sequence and in a single event.
Out of the box, Finance and Operations
includes approximately 250 data packages.
To load Out-of-the-Box data packages,
open Microsoft Dynamics Lifecycle Services,
also known as LCS,
and click the "Asset Library" tile.
Select Process Data Package as the asset type,
and then click "Import."
You can then select packages
based on the industry that you require.
After the data packaging
publishing process has been completed,
the relevant data package appears in
the Data Package Files List in the Asset Library.
Data packages that you load
multiple data entities at the same time.
For data entities that have dependencies on each other,
the import sequence is crucial for
successful and correct data loading.
The order that entities are loaded in is defined through
the entity sequence in the data project that you created.
When a user adds data entities to a data project,
a default sequence is set for entities.
The first entity that's added to the project
will be set as the first entity to load.
The next entity that's added will be second,
and the next entity will be third, and so on.
For example, a user adds three entities in
this order: customer group product filters,
customer groups, and vendor groups.
In this case, the customer group product filters entity
will be assigned an entity sequence of 1.1.1.
The customer groups entity will be
assigned an entity sequence of 1.1.2.
And the vendor groups entity will be assigned
an entity sequence of 1.1.3.
The rules for entity sequences are as follows:
Execution units run completely in
parallel and have no dependency on each other.
Within each execution unit,
the import is done one level
at a time in ascending order.
Within each level, the import is done
one sequence at a time in ascending order.
Entities that have the same execution unit,
level, and sequence are imported in parallel.
In our case, the customer group product filters entity
has a dependency on the customer groups entity.
Therefore, for data to be loaded successfully,
the customer group product filters entity
must be imported after the customer groups entity.
So the entity sequence should look like this.
Data entities are then
loaded based on a defined sequence.
>> This brings us to the end of this presentation.
We hope you found this information
useful. Thank you for watching.