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DATA REFRESH IN POWER BI

 * Article
 * 04/14/2023
 * 12 contributors

Feedback



IN THIS ARTICLE

Power BI enables you to go from data to insight to action quickly, yet you must
make sure the data in your Power BI reports and dashboards is recent. Knowing
how to refresh the data is often critical in delivering accurate results.

This article describes the data refresh features of Power BI and their
dependencies at a conceptual level. It also provides best practices and tips to
avoid common refresh issues. The content lays a foundation to help you
understand how data refresh works. For targeted step-by-step instructions to
configure data refresh, refer to the tutorials and how-to guides listed in the
Next steps section at the end of this article.


UNDERSTANDING DATA REFRESH

Embed Power BI content with service principal and an application secret

Whenever you refresh data, Power BI must query the underlying data sources,
possibly load the source data into a dataset, and then update any visualizations
in your reports or dashboards that rely on the updated dataset. The entire
process consists of multiple phases, depending on the storage modes of your
datasets, as explained in the following sections.

To understand how Power BI refreshes your datasets, reports, and dashboards, you
must be aware of the following concepts:

 * Storage modes and dataset types: The storage modes and dataset types that
   Power BI supports have different refresh requirements. You can choose between
   reimporting data into Power BI to see any changes that occurred or querying
   the data directly at the source.
 * Power BI refresh types: Regardless of dataset specifics, knowing the various
   refresh types can help you understand where Power BI might spend its time
   during a refresh operation. And combining these details with storage mode
   specifics helps to understand what exactly Power BI performs when you select
   Refresh now for a dataset.


STORAGE MODES AND DATASET TYPES

A Power BI dataset can operate in one of the following modes to access data from
various data sources. For more information, see Storage mode in Power BI
Desktop.

 * Import mode
 * DirectQuery mode
 * LiveConnect mode
 * Push mode

The following diagram illustrates the different data flows, based on storage
mode. The most significant point is that only Import mode datasets require a
source data refresh. They require refresh because only this type of dataset
imports data from its data sources, and the imported data might be updated on a
regular or ad-hoc basis. DirectQuery datasets and datasets in LiveConnect mode
to Analysis Services don't import data; they query the underlying data source
with every user interaction. Datasets in push mode don't access any data sources
directly but expect you to push the data into Power BI. Dataset refresh
requirements vary depending on the storage mode/dataset type.



DATASETS IN IMPORT MODE

Power BI imports the data from the original data sources into the dataset. Power
BI report and dashboard queries submitted to the dataset return results from the
imported tables and columns. You might consider such a dataset a point-in-time
copy. Because Power BI copies the data, you must refresh the dataset to fetch
changes from the underlying data sources.

When a dataset is refreshed, it's either fully refreshed or partially refreshed.
Partial refresh will take place in datasets that have tables with an incremental
refresh policy. In these datasets, only a subset of the table partitions are
refreshed. In addition, advanced users can use the XMLA endpoint to refresh
specific partitions in any dataset.

The amount of memory required to refresh a dataset depends on whether you're
performing a full or partial refresh. During the refresh, a copy of the dataset
is kept to handle queries to the dataset. This means that if you're performing a
full refresh, you'll need twice the amount of memory the dataset requires.

We recommend that you plan your capacity usage to ensure that the extra memory
needed for dataset refresh, is accounted for. Having enough memory prevents
refresh issues that can occur if your datasets require more memory than
available, during refresh operations. To find out how much memory is available
for each dataset on a Premium capacity, refer to the Capacities and SKUs table.

For more information about large datasets in Premium capacities, see large
datasets.

DATASETS IN DIRECTQUERY MODE

Power BI doesn't import data over connections that operate in DirectQuery mode.
Instead, the dataset returns results from the underlying data source whenever a
report or dashboard queries the dataset. Power BI transforms and forwards the
queries to the data source.

Note

Live connection reports submit queries to the capacity or Analysis Services
instance that hosts the dataset or the model. When using external analysis
services such as SQL Server Analysis Services (SSAS) or Azure Analysis Services
(AAS), resources are consumed outside of Power BI.

Because Power BI doesn't import the data, you don't need to run a data refresh.
However, Power BI still performs tile refreshes and possibly report refreshes,
as the next section on refresh types explains. A tile is a report visual pinned
to a dashboard, and dashboard tile refreshes happen about every hour so that the
tiles show recent results. You can change the schedule in the dataset settings,
as in the screenshot below, or force a dashboard update manually by using the
Refresh now option.



Note

 * Datasets in import mode and composite datasets that combine import mode and
   DirectQuery mode don't require a separate tile refresh, because Power BI
   refreshes the tiles automatically during each scheduled or on-demand data
   refresh. Datasets that are updated based on the XMLA endpoint will only clear
   the cached tile data (invalidate cache). The tile caches aren't refreshed
   until each user accesses the dashboard. For import models, you can find the
   refresh schedule in the "Scheduled refresh" section of the Datasets tab. For
   composite datasets, the "Scheduled refresh" section is located in the
   Optimize Performance section.
 * Power BI does not support cross-border live connections to Azure Analysis
   Services (AAS) in a sovereign cloud.

PUSH DATASETS

Push datasets don't contain a formal definition of a data source, so they don't
require you to perform a data refresh in Power BI. You refresh them by pushing
your data into the dataset through an external service or process, such as Azure
Stream Analytics. This is a common approach for real-time analytics with Power
BI. Power BI still performs cache refreshes for any tiles used on top of a push
dataset. For a detailed walkthrough, see Tutorial: Stream Analytics and Power
BI: A real-time analytics dashboard for streaming data.


POWER BI REFRESH TYPES

A Power BI refresh operation can consist of multiple refresh types, including
data refresh, OneDrive refresh, refresh of query caches, tile refresh, and
refresh of report visuals. While Power BI determines the required refresh steps
for a given dataset automatically, you should know how they contribute to the
complexity and duration of a refresh operation. For a quick reference, refer to
the following table.

Storage mode Data refresh OneDrive refresh Query caches Tile refresh Report
visuals Import Scheduled and on-demand Yes, for connected datasets If enabled on
Premium capacity Automatically and on-demand No DirectQuery Not applicable Yes,
for connected datasets If enabled on Premium capacity Automatically and
on-demand No LiveConnect Not applicable Yes, for connected datasets If enabled
on Premium capacity Automatically and on-demand Yes Push Not applicable Not
applicable Not practical Automatically and on-demand No

Another way to consider the different refresh types is what they impact and
where you can apply them. Changes in data source table structure, or schema,
such as a new, renamed, or removed column can only be applied in Power BI
Desktop, and in the Power BI service they can cause the refresh to fail. For a
quick reference on what they impact, refer to the following table.


Refresh of report visuals Data refresh Schema refresh What do the different
refresh types do? Queries used to populate visuals are refreshed.

For visuals using DirectQuery tables the visual will query to get the latest
data from the data source.

For visuals using imported tables the visual will only query data already
imported to the dataset on the last data refresh. Data is refreshed from the
data source.

Doesn't apply to DirectQuery tables as they are at the visual level and rely on
refresh of report visuals.

For imported tables the data is refreshed from the source. Any data source table
structure change since previous refresh will show.

For example: To show a new column added to a Power BI Dataflow or SQL Database
view.

Applies to both imported and DirectQuery tables.

In Power BI Desktop refresh of report visuals, data refresh, and schema refresh
all happen together using

 * Home ribbon > Refresh button
 * Home ribbon > Transform data > Close & Apply button
 * The context menu (right-click or select the ellipsis) on any table then
   choosing Refresh data

These refresh types cannot always be applied independently, and where you can
apply them is different in Power BI Desktop and the Power BI service. For a
quick reference, refer to the following table.


Refresh of report visuals Data refresh Schema refresh In Power BI Desktop
 * View ribbon > Performance Analyzer button > Refresh visuals
 * Creating and changing visuals causing a DAX query to run
 * When Page Refresh is turned on (DirectQuery only)
 * Opening the PBIX file

Not available independently from other refresh types Not available independently
from other refresh types In the Power BI service
 * When the browser loads or reloads the report
 * Clicking the Refresh Visuals top right menu bar button
 * Clicking the Refresh button in edit mode
 * When Page Refresh is turned on (DirectQuery only)

 * Scheduled refresh
 * Refresh now
 * Refresh a Power BI dataset from Power Automate
 * Processing the table from SQL Server Management Studio (Premium)

Not available Keep in mind For example, if you open a report in the browser,
then the scheduled refresh performs a data refresh of the imported tables, the
report visuals in the open browser won't update until a refresh of report
visuals is initiated. Data refresh on the Power BI service will fail when the
source column or table is renamed or removed. It fails because the Power BI
service doesn't also include a schema refresh. To correct this error, a schema
refresh needs to happen in Power BI Desktop and the dataset republished to the
service. A renamed or removed column or table at the data source will be updated
with a schema refresh in Power BI Desktop, but it can break visuals and DAX
expressions (measures, calculated columns, row level security, etc.), as well as
remove relationships, that are dependent on those columns or tables.

DATA REFRESH

For Power BI users, refreshing data typically means importing data from the
original data sources into a dataset, either based on a refresh schedule or
on-demand. You can perform multiple dataset refreshes daily, which might be
necessary if the underlying source data changes frequently. Power BI limits
datasets on shared capacity to eight scheduled daily dataset refreshes. The
eight time values are stored in the backend database and are based on the local
time zone that was selected on the Dataset Settings page. The scheduler checks
which model should be refreshed and at what time(s). The quota of eight
refreshes resets daily at 12:01 a.m. local time.



If the dataset resides on a Premium capacity, you can schedule up to 48
refreshes per day in the dataset settings. For more information, see Configure
scheduled refresh later in this article. Datasets on a Premium capacity with the
XMLA endpoint enabled for read-write support unlimited refresh operations when
configured programmatically with TMSL or PowerShell.

It's also important to call out that the shared-capacity limitation for daily
refreshes applies to both scheduled refreshes and API refreshes combined. You
can also trigger an on-demand refresh by selecting Refresh now in the dataset
menu, as the following screenshot depicts. On-demand refreshes aren't included
in the refresh limitation. Also note that datasets on a Premium capacity don't
impose limitations for API refreshes. If you're interested in building your own
refresh solution by using the Power BI REST API, see Datasets - Refresh Dataset.



Note

Data refreshes must complete in less than 2 hours on shared capacity. If your
datasets require longer refresh operations, consider moving the dataset onto a
Premium capacity. On Premium, the maximum refresh duration is 5 hours.

ONEDRIVE REFRESH

If you created your datasets and reports based on a Power BI Desktop file, Excel
workbook, or comma separated value (.csv) file on OneDrive or SharePoint Online,
Power BI performs another type of refresh, known as OneDrive refresh. For more
information, see Get data from files for Power BI.

Unlike a dataset refresh during which Power BI imports data from a data source
into a dataset, OneDrive refresh synchronizes datasets and reports with their
source files. By default, Power BI checks about every hour if a dataset
connected to a file on OneDrive or SharePoint Online requires synchronization.

Power BI performs refresh based on an item ID in OneDrive, so be thoughtful when
considering updates versus replacement. When you set a OneDrive file as the data
source, Power BI references the item ID of the file when it performs the
refresh. Consider the following scenario: you have a master file A and a
production copy of that file B, and you configure OneDrive refresh for file B.
If you then copy file A over file B, the copy operation deletes the old file B
and creates a new file B with a different item ID, which breaks OneDrive
refresh. To avoid that situation, you can instead upload and replace file B,
which keeps its same item ID.

You can move the file to another location (using drag and drop, for example) and
refresh will continue to work because Power BI still knows the file ID. However,
if you copy that file to another location, a new instance of the file and a new
fileID is created. Therefore, your Power BI file reference is no longer valid
and refresh will fail.

Note

It can take Power BI up to 60 minutes to refresh a dataset, even once the sync
has completed on your local machine and after you've used Refresh now in the
Power BI service.

To review past synchronization cycles, check the OneDrive tab in the refresh
history. The following screenshot shows a completed synchronization cycle for a
sample dataset.



As the above screenshot shows, Power BI identified this OneDrive refresh as a
Scheduled refresh, but it isn't possible to configure the refresh interval. You
can only deactivate OneDrive refresh in the dataset's settings. Deactivating
refresh is useful if you don't want your datasets and reports in Power BI to
pick up any changes from the source files automatically.

The dataset settings page only shows the OneDrive Credentials and OneDrive
refresh sections if the dataset is connected to a file in OneDrive or SharePoint
Online, as in the following screenshot. Datasets that aren't connected to
sources file in OneDrive or SharePoint Online don't show these sections.



If you disable OneDrive refresh for a dataset, you can still synchronize your
dataset on-demand by selecting Refresh now in the dataset menu. As part of the
on-demand refresh, Power BI checks if the source file on OneDrive or SharePoint
Online is newer than the dataset in Power BI and synchronizes the dataset if so.
The Refresh history lists these activities as on-demand refreshes on the
OneDrive tab.

Keep in mind that OneDrive refresh doesn't pull data from the original data
sources. OneDrive refresh simply updates the resources in Power BI with the
metadata and data from the .pbix, .xlsx, or .csv file, as the following diagram
illustrates. To ensure that the dataset has the most recent data from the data
sources, Power BI also triggers a data refresh as part of an on-demand refresh.
You can verify this in the Refresh history if you switch to the Scheduled tab.



If you keep OneDrive refresh enabled for a OneDrive or SharePoint
Online-connected dataset and you want to perform data refresh on a scheduled
basis, make sure you configure the schedule so that Power BI performs the data
refresh after the OneDrive refresh. For example, if you created your own service
or process to update the source file in OneDrive or SharePoint Online every
night at 1 am, you could configure scheduled refresh for 2:30 am to give Power
BI enough time to complete the OneDrive refresh before starting the data
refresh.

REFRESH OF QUERY CACHES

If your dataset resides on a Premium capacity, you might be able to improve the
performance of any associated reports and dashboards by enabling query caching,
as in the following screenshot. Query caching instructs the Premium capacity to
use its local caching service to maintain query results, avoiding having the
underlying data source compute those results. For more information, see Query
caching in Power BI Premium.



Following a data refresh, however, previously cached query results are no longer
valid. Power BI discards these cached results and must rebuild them. For this
reason, query caching might not be as beneficial for reports and dashboards
associated with datasets that you refresh often, for example 48 times per day.

REFRESH OF REPORT VISUALS

This refresh process is less important because it's only relevant for live
connections to Analysis Services. For these connections, Power BI caches the
last state of the report visuals so that when you view the report again, Power
BI doesn't have to query the Analysis Services tabular model. When you interact
with the report, such as by changing a report filter, Power BI queries the
tabular model and updates the report visuals automatically. If you suspect that
a report is showing stale data, you can also select the Refresh button of the
report to trigger a refresh of all report visuals, as the following screenshot
illustrates.



Only pinned visuals are refreshed, not pinned live pages. To refresh a pinned
live page, you can use the browser's Refresh button.


REVIEW DATA INFRASTRUCTURE DEPENDENCIES

Regardless of storage modes, no data refresh can succeed unless the underlying
data sources are accessible. There are three main data access scenarios:

 * A dataset uses data sources that reside on-premises
 * A dataset uses data sources in the cloud
 * A dataset uses data from both, on-premises and cloud sources


CONNECTING TO ON-PREMISES DATA SOURCES

If your dataset uses a data source that Power BI can't access over a direct
network connection, you must configure a gateway connection for this dataset
before you can enable a refresh schedule or perform an on-demand data refresh.
For more information about data gateways and how they work, see What are
on-premises data gateways?

You have the following options:

 * Choose an enterprise data gateway with the required data source definition
 * Deploy a personal data gateway

Note

You can find a list of data source types that require a data gateway in the
article Manage your data source - Import/Scheduled Refresh.

USING AN ENTERPRISE DATA GATEWAY

Microsoft recommends using an enterprise data gateway instead of a personal
gateway to connect a dataset to an on-premises data source. Make sure the
gateway is properly configured, which means the gateway must have the latest
updates and all required data source definitions. A data source definition
provides Power BI with the connection information for a given source, including
connection endpoints, authentication mode, and credentials. For more information
about managing data sources on a gateway, see Manage your data source -
import/scheduled refresh.

Connecting a dataset to an enterprise gateway is relatively straightforward if
you're a gateway administrator. With admin permissions, you can promptly update
the gateway and add missing data sources, if necessary. In fact, you can add a
missing data source to your gateway straight from the dataset settings page.
Expand the toggle button to view the data sources and select the Add to gateway
link, as in the following screenshot. If you aren't a gateway administrator, on
the other hand, you must contact a gateway admin to add the required data source
definition.

Note

Only gateway admins can add data sources to a gateway. Also make sure your
gateway admin adds your user account to the list of users with permissions to
use the data source. The dataset settings page only lets you select an
enterprise gateway with a matching data source that you have permission to use.



Make sure you map the correct data source definition to your data source. As the
above screenshot illustrates, gateway admins can create multiple definitions on
a single gateway connecting to the same data source, each with different
credentials. In the example shown, a dataset owner in the Sales department would
choose the AdventureWorksProducts-Sales data source definition while a dataset
owner in the Support department would map the dataset to the
AdventureWorksProducts-Support data source definition. If the names of the data
source definition aren't intuitive, contact your gateway admin to clarify which
definition to pick.

Note

A dataset can only use a single gateway connection. In other words, it is not
possible to access on-premises data sources across multiple gateway connections.
Accordingly, you must add all required data source definitions to the same
gateway.

DEPLOYING A PERSONAL DATA GATEWAY

If you have no access to an enterprise data gateway and you're the only person
who manages datasets so you don't need to share data sources with others, you
can deploy a data gateway in personal mode. In the Gateway connection section,
under You have no personal gateways installed , select Install now. The personal
data gateway has several limitations as documented in On-premises data gateway
(personal mode).

Unlike for an enterprise data gateway, you don't need to add data source
definitions to a personal gateway. Instead, you manage the data source
configuration by using the Data source credentials section in the dataset
settings, as the following screenshot illustrates.




ACCESSING CLOUD DATA SOURCES

Datasets that use cloud data sources, such as Azure SQL DB, don't require a data
gateway if Power BI can establish a direct network connection to the source.
Accordingly, you can manage the configuration of these data sources by using the
Data source credentials section in the dataset settings. As the following
screenshot shows, you don't need to configure a gateway connection.



Note

Each user can only have one set of credentials per data source, across all of
the datasets they own, regardless of the workspaces where the datasets reside.
And each dataset can only have one owner. If your want to update the credentials
for a dataset where you are not the dataset owner, you must first take over the
dataset by clicking on the Take Over button on the dataset settings page.


ACCESSING ON-PREMISES AND CLOUD SOURCES IN THE SAME SOURCE QUERY

A dataset can get data from multiple sources, and these sources can reside
on-premises or in the cloud. However, a dataset can only use a single gateway
connection, as mentioned earlier. While cloud data sources don't necessarily
require a gateway, a gateway is required if a dataset connects to both
on-premises and cloud sources in a single mashup query. In this scenario, Power
BI must use a gateway for the cloud data sources as well. The following diagram
illustrates how such a dataset accesses its data sources.



Note

If a dataset uses separate mashup queries to connect to on-premises and cloud
sources, Power BI uses a gateway connection to reach the on-premises sources and
a direct network connection to the cloud sources. If a mashup query merges or
appends data from on-premises and cloud sources, Power BI switches to the
gateway connection even for the cloud sources.

Power BI datasets rely on Power Query to access and retrieve source data. The
following mashup listing shows a basic example of a query that merges data from
an on-premises source and a cloud source.

Let

    OnPremSource = Sql.Database("on-premises-db", "AdventureWorks"),

    CloudSource = Sql.Databases("cloudsql.database.windows.net", "AdventureWorks"),

    TableData1 = OnPremSource{[Schema="Sales",Item="Customer"]}[Data],

    TableData2 = CloudSource {[Schema="Sales",Item="Customer"]}[Data],

    MergedData = Table.NestedJoin(TableData1, {"BusinessEntityID"}, TableData2, {"BusinessEntityID"}, "MergedData", JoinKind.Inner)

in

    MergedData


There are two options to configure a data gateway to support merging or
appending data from on-premises and cloud sources:

 * Add a data source definition for the cloud source to the data gateway in
   addition to the on-premises data sources.
 * Enable the checkbox Allow user's cloud data sources to refresh through this
   gateway cluster.



If you enable the checkbox Allow user's cloud data sources to refresh through
this gateway cluster in the gateway configuration, as in the screenshot above,
Power BI can use the configuration that the user defined for the cloud source
under Data source credentials in the dataset settings. This can help to lower
the gateway configuration overhead. On the other hand, if you want to have
greater control over the connections that your gateway establishes, you
shouldn't enable this checkbox. In this case, you must add an explicit data
source definition for every cloud source that you want to support to your
gateway. It's also possible to enable the checkbox and add explicit data source
definitions for your cloud sources to a gateway. In this case, the gateway uses
the data source definitions for all matching sources.


CONFIGURING QUERY PARAMETERS

The mashup or M queries you create by using Power Query can vary in complexity
from trivial steps to parameterized constructs. The following listing shows a
small sample mashup query that uses two parameters called SchemaName and
TableName to access a given table in an AdventureWorks database.

let

    Source = Sql.Database("SqlServer01", "AdventureWorks"),

    TableData = Source{[Schema=SchemaName,Item=TableName]}[Data]

in

    TableData


Note

Query parameters are only supported for Import mode datasets.
DirectQuery/LiveConnect mode does not support query parameter definitions.

To ensure that a parameterized dataset accesses the correct data, you must
configure the mashup query parameters in the dataset settings. You can also
update the parameters programmatically by using the Power BI REST API. The
following screenshot shows the user interface to configure the query parameters
for a dataset that uses the above mashup query.




REFRESH AND DYNAMIC DATA SOURCES

A dynamic data source is a data source in which some or all of the information
required to connect can't be determined until Power Query runs its query,
because the data is generated in code or returned from another data source.
Examples include: the instance name and database of a SQL Server database; the
path of a CSV file; or the URL of a web service.

In most cases, Power BI datasets that use dynamic data sources can't be
refreshed in the Power BI service. There are a few exceptions in which dynamic
data sources can be refreshed in the Power BI service, such as when using the
RelativePath and Query options with the Web.Contents M function. Queries that
reference Power Query parameters can also be refreshed.

To determine whether your dynamic data source can be refreshed, open the Data
Source Settings dialog in Power Query Editor, and then select Data Sources In
Current File. In the window that appears, look for the following warning
message, as shown in the following image:

Note

Some data sources may not be listed because of hand-authored queries.



If that warning is present in the Data Source Settings dialog that appears, then
a dynamic data source that can't be refreshed in the Power BI service is
present.


CONFIGURE SCHEDULED REFRESH

Establishing connectivity between Power BI and your data sources is by far the
most challenging task in configuring a data refresh. The remaining steps are
relatively straightforward and include setting the refresh schedule and enabling
refresh failure notifications. For step-by-step instructions, see the how-to
guide Configuring scheduled refresh.


SETTING A REFRESH SCHEDULE

The Scheduled refresh section is where you define the frequency and time slots
to refresh a dataset. As mentioned earlier, you can configure up to eight daily
time slots if your dataset is on shared capacity, or 48 time slots on Power BI
Premium. The following screenshot shows a refresh schedule on a twelve-hour
interval.



Having configured a refresh schedule, the dataset settings page informs you
about the next refresh time, as in the screenshot above. If you want to refresh
the data sooner, such as to test your gateway and data source configuration,
perform an on-demand refresh by using the Refresh Now option in the dataset menu
in the nav pane. On-demand refreshes don't affect the next scheduled refresh
time.

Tip

Power BI does not have a monthly refresh interval option. However, you can use
Power Automate to create a custom refresh interval that occurs monthly, as
described in the following Power BI blog post.

Note also that the configured refresh time might not be the exact time when
Power BI starts the next scheduled process. Power BI starts scheduled refreshes
on a best effort basis. The target is to initiate the refresh within 15 minutes
of the scheduled time slot, but a delay of up to one hour can occur if the
service can't allocate the required resources sooner.

Note

Power BI deactivates your refresh schedule after four consecutive failures or
when the service detects an unrecoverable error that requires a configuration
update, such as invalid or expired credentials. It is not possible to change the
consecutive failures threshold.


GETTING REFRESH FAILURE NOTIFICATIONS

By default, Power BI sends refresh failure notifications through email to the
dataset owner so that the owner can act in a timely manner should refresh issues
occur. Power BI also sends you a notification when the service disables your
schedule due to consecutive failures. Microsoft recommends that you leave the
checkbox Send refresh failure notification emails dataset owner enabled.

It's also a good idea to specify additional recipients by using the Email these
contacts when the refresh fails textbox. The specified recipients receive
refresh failure notifications in addition to the dataset owner. This might be a
colleague taking care of your datasets while you are on vacation. It could also
be the email alias of your support team taking care of refresh issues for your
department or organization. Sending refresh failure notifications to others in
addition to the dataset owner is helpful to ensure issues get noticed and
addressed in a timely manner.

Note that Power BI not only sends notifications on refresh failures but also
when the service pauses a scheduled refresh due to inactivity. After two months,
when no user has visited any dashboard or report built on the dataset, Power BI
considers the dataset inactive. In this situation, Power BI sends an email
message to the dataset owner indicating that the service paused the refresh
schedule for the dataset. See the following screenshot for an example of such a
notification.



To resume scheduled refresh, visit a report or dashboard built using this
dataset or manually refresh the dataset using the Refresh Now option.

Note

Sending refresh notifications to external users is not supported. The recipients
you specify in the Email these users when the refresh fails textbox must have
accounts in your Azure Active Directory tenant. This limitation applies to both
dataset refresh and dataflow refresh.


CHECKING REFRESH STATUS AND HISTORY

In addition to failure notifications, it's a good idea to check your datasets
periodically for refresh errors. A quick way is to view the list of datasets in
a workspace. Datasets with errors show a small warning icon. Select the warning
icon to obtain additional information, as in the following screenshot. For more
information about troubleshooting specific refresh errors, see Troubleshooting
refresh scenarios.



The warning icon helps to indicate current dataset issues, but it's also a good
idea to check the refresh history occasionally. As the name implies, the refresh
history enables you to review the success or failure status of past
synchronization cycles. For example, a gateway administrator might have updated
an expired set of database credentials. As you can see in the following
screenshot, the refresh history shows when an affected refresh started working
again.



Note

You can find a link to display the refresh history in the dataset settings. You
can also retrieve the refresh history programmatically by using the Power BI
REST API. By using a custom solution, you can monitor the refresh history of
multiple datasets in a centralized way.


AUTOMATIC PAGE REFRESH

Automatic page refresh works at a report page level, and allows report authors
to set a refresh interval for visuals in a page that is only active when the
page is being consumed. Automatic page refresh is only available for DirectQuery
data sources. The minimum refresh interval depends on which type of workspace
the report is published in, and the capacity admin settings for Premium
workspaces and embedded workspaces.

Learn more about automatic page refresh in the automatic page refresh article.


REFRESH CANCELLATION

Stopping a dataset refresh is useful when you want to stop a refresh of a large
dataset during peak time. Use the refresh cancellation feature to stop
refreshing datasets that reside on Premium, Premium Per User (PPU) or Power BI
Embedded capacities.

To cancel a dataset refresh, you need to be a contributor, member or an admin of
the dataset's workspace. Dataset refresh cancellation only works with datasets
that use import mode or composite mode.

Note

Datasets created as part of datamarts aren't supported.

To start a refresh go to the dataset you want to refresh, and select Refresh
now.



To stop a refresh follow these steps:

 1. Go to the dataset that's refreshing and select Cancel refresh.
    
    

 2. In the Cancel refresh pop-up window, select Yes.
    
    


BEST PRACTICES

Checking the refresh history of your datasets regularly is one of the most
important best practices you can adopt to ensure that your reports and
dashboards use current data. If you discover issues, address them promptly and
follow up with data source owners and gateway administrators if necessary.

In addition, consider the following recommendations to establish and maintain
reliable data refresh processes for your datasets:

 * Schedule your refreshes for less busy times, especially if your datasets are
   on Power BI Premium. If you distribute the refresh cycles for your datasets
   across a broader time window, you can help to avoid peaks that might
   otherwise overtax available resources. Delays starting a refresh cycle are an
   indicator of resource overload. If a Premium capacity is exhausted, Power BI
   might even skip a refresh cycle.
 * Keep refresh limits in mind. If the source data changes frequently or the
   data volume is substantial, consider using DirectQuery/LiveConnect mode
   instead of Import mode if the increased load at the source and the impact on
   query performance are acceptable. Avoid constantly refreshing an Import mode
   dataset. However, DirectQuery/LiveConnect mode has several limitations, such
   as a one-million-row limit for returning data and a 225-seconds response time
   limit for running queries, as documented in Use DirectQuery in Power BI
   Desktop. These limitations might require you to use Import mode nonetheless.
   For large data volumes, consider the use of aggregations in Power BI.
 * Verify that your dataset refresh time doesn't exceed the maximum refresh
   duration. Use Power BI Desktop to check the refresh duration. If it takes
   more than 2 hours, consider moving your dataset to Power BI Premium. Your
   dataset might not be refreshable on shared capacity. Also consider using
   Incremental refresh for datasets that are larger than 1 GB or take several
   hours to refresh.
 * Optimize your datasets to include only those tables and columns that your
   reports and dashboards use. Optimize your mashup queries and, if possible,
   avoid dynamic data source definitions and expensive DAX calculations.
   Specifically avoid DAX functions that test every row in a table because of
   the high memory consumption and processing overhead.
 * Apply the same privacy settings as in Power BI Desktop to ensure that Power
   BI can generate efficient source queries. Keep in mind that Power BI Desktop
   does not publish privacy settings. You must manually reapply the settings in
   the data source definitions after publishing your dataset.
 * Limit the number of visuals on your dashboards, especially if you use
   row-level security (RLS). As explained earlier in this article, an excessive
   number of dashboard tiles can significantly increase the refresh duration.
 * Use a reliable enterprise data gateway deployment to connect your datasets to
   on-premises data sources. If you notice gateway-related refresh failures,
   such as gateway unavailable or overloaded, follow up with gateway
   administrators to either add additional gateways to an existing cluster or
   deploy a new cluster (scale up versus scale out).
 * Use separate data gateways for Import datasets and DirectQuery/LiveConnect
   datasets so that the data imports during scheduled refresh don't impact the
   performance of reports and dashboards on top of DirectQuery/LiveConnect
   datasets, which query the data sources with each user interaction.
 * Ensure that Power BI can send refresh failure notifications to your mailbox.
   Spam filters might block the email messages or move them into a separate
   folder where you might not notice them immediately.


NEXT STEPS

Configuring scheduled refresh
Tools for troubleshooting refresh issues
Troubleshooting refresh scenarios

More questions? Try asking the Power BI Community





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