>> Hello and welcome to the Power BI, August 2021 update.
In this video, we'll explore what's new
this month and see some demos of the highlights.
We have some exciting new features
for you in the reporting section.
First, you can now customize the formatting
of shapes you add to your Power BI reports.
We've added a number of controls into the shape card of
the formatting pane for
a variety of different shape options,
including rounded rectangles, chevrons, arrows, and more.
Now, you can customize and look
at each of these shapes you create,
helping you to more flexibly design,
structure, and stylize your report pages.
Next, since we introduced the x-axis constant line,
we've received feedback on ways we can make it an even
more useful reference on your Cartesian charts.
This month, we've acted on that feedback,
bringing you conditional formatting for
x-axis constant line value and shading
for regions before or after the constant line.
You can now find these new options in
the X-axis constant line guard in the analytics pane.
This month security administrators
can define a default label to be set on
a PBIX file when a user creates
a new file or edits an existing file that has no label.
Users can change the default label as they see fit.
Moving forward, default label policies will be
applicable to new content
in the Power BI service as well.
In the analytics section,
we're happy to announce that we now support
sharing synonyms for everyone in your organization.
Field synonyms are an important part of Q&A because
users often have a variety of
terms they use to refer to the same field,
such as total sales,
net sales, and total net sales.
Now you can leverage your coworkers' synonyms and
minimize duplicate efforts when
adding synonyms to your models.
Next, we have several new updates
for you in the modeling section.
First, we're introducing a new way to express
date and datetime type values as a DAX literal.
This will allow you to directly
specify dates and times up to the
second in your DAX queries
without having to use other functions.
Starting with this release,
we support either a complete data value
or a complete date and time value.
Jeroen will show us a demo of this feature.
>> We're introducing a new way to
express date and datetime values in DAX.
This allows you to directly specify dates and times in
your DAX statements without
having to use functions such as date,
date value, time, and time value.
For example, I can specify a date time now
using this new construct called literals,
by specifying "dt,
" and then the date and time that I would like to get.
As you can see here in line 2 of my DAX statement,
I specify var DT_literal,
which uses the new construct.
I've also included line 3 and 4 where I specified
two other vars that return exactly the same value,
but then using the dates and time or
the date value and time value functions.
As you can see, this is a new way of
specifying those date and time values in your DAX.
As a more practical example,
let's say I'm interested in a table of orders in 2019.
I can specify this using
the filter function on the Internet sales and say,
all of this needs to be larger than this date
and less than the other date.
I can specify that using date and time functions.
I can do exactly the same using these new literals.
I can say, filter Internet sales,
order date larger than "dt',
date and time, and smaller than "dt", date and time.
Although we're introducing this new way
of specifying date times which
we believe makes your code easier to write and to read,
it's of course entirely up to you what you want to use.
>> Next, we've added
new configuration options to Power BI Desktop to optimize
query performance when importing data or when using
direct query by evaluating tables simultaneously.
While Power BI Desktop does this automatically,
sometimes you might want to
influence the behavior yourself.
We've added an option to set the maximum number of
simultaneous query evaluations in direct query,
and an option to set
the maximum memory used for simultaneous evaluation.
Jeroen will show us a demo of these new capabilities.
>> Power BI Desktop optimizes
query performance when importing
data or when using direct query
by evaluating tables simultaneously.
However, in specific situations you might want
to influence the behavior and change the defaults.
For example, when the data import is taking too long
or if Power BI Desktop is
taking too much resources to your liking.
Until now, you could only influence
these settings by making changes to the registry.
But starting this month,
we've added these two configuration options
to Power BI Desktop,
which you can find by going into Options,
and then under Global, select "Data Load".
You will find the settings under
the loading tables simultaneously header.
There's two settings here,
maximum number of simultaneous evaluations,
this controls the level of
parallelization for query execution.
Then the other option is
the maximum number per simultaneous evaluation.
This configures the available memory per query.
We set the defaults,
and you can also learn on how we
set the defaults and got some recommendation by
hovering over the tooltips and reading
some more on the Learn More link that we supply.
Using these settings, you can make
sure that the loading of the data
is optimized for your machine so
you get the best experience.
>> In the data connectivity section,
we have several new and
updated connectors for you this month.
First, we are happy to announce
an update to dataflow connectors in Power BI,
and the consolidation of
the two existing dataflow connectors
into a single connector.
Dataflow customers will now be able to
leverage a single connector to discover,
navigate, and get data from dataflows created in
either Power BI workspaces or Power Apps environments.
In addition, the new connector will provide
Power BI premium dataflow customers with
improved performance when authoring dataflows or
datasets by leveraging
Power BI's enhanced compute engine.
Next, we are excited to announce the release of
the autonomy data analytics connector by Ace Royalty.
Autonomy provides integrated software and
data solutions for process automation.
The automate connector for Power BI enables
you to combine multiple data from workflows and
processes into a single data layout
on-demand without copying or moving data.
The connector can be found in
the online services category of the Git data dialogue.
We've also made updates to the Azure Databricks,
Dremio, Google BigQuery,
and QuickBase connectors,
expecting improvements in experience and
performance as well as new capabilities.
To learn more about these updates,
check out the blog post for this month.
We have some exciting new changes
for you in this service section.
First, you can now set
MIP sensitivity labels on
paginated reports in the Power BI service,
just like you can on Power BI reports.
When data from a paginated report is
exported to a Word, Excel, PowerPoint,
or PDF file,
the report's label and protection settings
will be applied to the exported file.
Next, you can now leverage
automatic aggregations to enhance
performance over DirectQuery datasets.
These create aggregations based
on user's historic query patterns.
Using machine learning,
automatic aggregations determine,
create, and maintain the most optimal set
of aggregations for users' workloads.
Users no longer need to have
extensive data modeling or
advanced query optimization experience,
and can leverage this feature with just a few clicks.
Christian will show us a demo of this feature.
>> Hello everybody. Automatic congregations
is based on the existing aggregations feature.
Which is really a remarkable feature
because if you think about it,
most business intelligence queries
are aggregated in nature.
Therefore, if you cache data at
the aggregated level, it stands to reason,
you will get a high bang for the buck
in terms of boosting query performance.
If the user happens to drill down to
the detail level, that's okay.
The system reverts to DirectQuery on the fly.
Now, the challenge with aggregations
till now has been that it
requires query optimization skills.
Well, we are removing this challenge,
because we will create the aggregations for you.
At the flick of a switch,
we will analyze historical query logs and identify
strategic aggregations that work
over any of the major data warehouses.
Let me demonstrate.
This is the New York taxi dataset.
I'm going to refresh the visuals.
This is over three billion rows in
Azure Synapses and pure DirectQuery.
If you think about the volume of data
coming back, and more importantly,
the complexity of the queries required for this report,
the query performance is actually quite reasonable.
But we know that business users in Power BI expect
instant response times for
snappy data-driven decision-making,
so there is certainly room for improvement.
As you can see, one of the visuals took
over 30 seconds to refresh.
This is in milliseconds.
If I interact with visuals on this report,
further queries are generated,
and the experience is a little sluggish. What can we do?
We can come into the dataset settings,
and we can enable automatic aggregations.
We can also set up a refresh schedule
that will not only refresh the aggregations,
but it will also redefine them if
required based on unforeseen query usage patterns.
This is what makes this a self-learning,
self-optimizing system.
Here's an instance of the report that's pointing
at the dataset that's already been set up.
As you can see, the query performance is much
improved at just over one second,
I get nice interactivity.
If I happen to perform an action that generates
a query that does not have an aggregation prepared,
the system will revert to DirectQuery
on the fly and it will keep track
of that query so that hopefully the
next time a user performs that interaction,
there will be an aggregation prepared.
As you can see, the query response time
is dramatically improved.
But as the dataset owner,
I want visibility of how much I'm
moving the needle across the entire business.
So I'm going to come back into
the dataset settings for
the dataset that's already set up,
and I get this beautiful lift chart that
shows me that in pure DirectQuery mode,
I'm at the 60th percentile in terms of
meeting my five-second query response time SLA.
With automatic aggregations enabled,
I'm up at the 80th percentile,
and I can dynamically adjust the number of
historical queries that will hit the aggregated cache to,
for example, 85 percent.
That will get me up to the 88th percentile,
and I can trade that off
versus the number of aggregations that will be
refreshed so I get good visibility
and I can understand the benefits of the feature.
>> This month, we're also very
excited to announce the public preview of
the new REST API to query
datasets in Power BI by using DAX.
Among other things, this new DAX REST API helps to
address customer feedback concerning
programmatic access to data in a dataset.
The new DAX REST API
avoids dependencies on Analysis Services,
client libraries requires no connection
to XMLA endpoints,
and works in Power BI premium as
well as in Power BI shared capacity.
To learn more about this powerful new interface,
check out this month's release blog post.
Next, workspace administrators can
now enable collection of
Power BI user activities and
metrics for any premium workspaces they own.
This preview capability
provides new real-time information
reported by the analysis services' engine
about dataset activity.
This allows you to monitor load, observe usage trends,
spot periods of unusual activity,
and identify performance degradation with
queries or dataset refresh operations.
We have partnered with
Azure Log Analytics to allow you to send
your Power BI activity data
to your own Azure environment.
This gives you up to two years of
data retention with ad hoc query and alerting.
We've even published a template report
to allow you to get insights on
your activity data right away without
having to parse and transform the log data yourself.
To learn more, check out
the announcement post and documentation for the feature.
In the mobile section,
we've updated the report footer to make
it easier to find and understand
all of the various actions you can perform
while consuming reports on Power BI mobile.
In the visualization section,
our embedded store is getting a new look.
Now, you can browse all of
the visuals allowed in your organization.
Try out the new experience,
and please let us know what you think.
We also have several exciting, new,
and updated visuals available for you on AppSource.
New this month are:
The Floor Plan Visual by Simpson Associates,
The Timeline Box Visual by TheraTraq,
The Timeline Basic Visual by TheraTraq,
The Phrazor Visual by vPhrase Analytics Solutions,
and The Balance Sheet Visual by K Team Solutions, GMBH.
Updated this month are the timeline visual by Queryon,
the Drill Down Graph PRO Visual by ZoomCharts,
and The BIpm custom visual by ProcessM.
This month's editors picks are:
The Drill Down Map PRO Visual by ZoomCharts,
The Craydec Timelines Visual by Craydec,
The KPI Ticker by MAQ Software,
and The Collage Visual by CloudScope.
You can find these editors picks and all of
the other mentioned visuals on AppSource.
That's all for this month.
As always, we hope you enjoy the updates,
and please keep sending us feedback on
what you'd like to see in upcoming releases.
Thanks for watching, and we'll see you again next month.