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- [Speaker] Let's take a look at how Power BI
is infusing AI driven
insights everywhere that people get work done.
Let's start in PowerPoint where my boss Kim and I
were working on a monthly business review deck
for our hotel and resorts company.
We want to help our team dive into the data
for who are our customers
and what is driving repeat visits to our properties.
Kim's left a comment asking me to add the data for
a demographics breakdown of our customers.
Fortunately, I have a Power Bear report with just this data.
We all know that copy/pasting data in charts into
PowerPoint can be a huge pain,
but now with just a couple of clicks,
I can add my report as a live, interactive
part of my presentations
with Power BI integration fully built into PowerPoint.
This is amazing for things like monthly business reviews.
Now, all we have to do is open PowerPoint each month
and refresh to see the latest data.
I'm gonna quickly adjust the look and feel of the report.
It works natively with animations,
layering with other shapes,
and most importantly in presentation mode.
Now, when we're presenting to our team,
we can interact with the report
and answer questions on the fly.
It's a great way to deliver data-driven storytelling
and keep meetings interactive.
This not only includes just slicing and dicing the data,
but in this report we've included Q&A as well.
So we can use natural language to get answers.
So if an executive or other meeting participant
has a question to the presenter,
they can answer it in real time.
For example, let's say someone asks
how many customers we had from Australia
and maybe wants to see it broken down by age group
and who purchased SPA package.
And just like that,
we can look up the answer right as part of our presentation.
but it doesn't stop there.
Let's say I want to include a textual summary of some
insights about my data right here in the slide.
To help me do this more quickly,
we've built in an option to automatically find insights
and generate a text narrative about your data.
I can simply click the data insights option
and Power BI will automatically look at the data
in your report page
and generate a textural summary
of the insights we find.
With one click,
I can paste the output right into the slide
where I can arrange and edit it as I like.
Here we can see the AI is highlighting what countries
our customers are coming from.
Some interesting differences
in the rate of returning customers
and an insight about the most common age group.
This type of content generation is a huge time saver
for building out a presentation.
Next, I want to show you another AI feature
built into Power BI
that we're gonna use in this monthly business review.
The key influencers is visual.
Key influencers is gonna help us understand the key
factors for if our customers return or not.
This is an awesome way for my team to see and understand
insights we can use to adjust our plans.
For example, customers who are booking sports and spa
packages are more likely to return
as well as those coming from certain locations.
To achieve this, Power BI is automatically building
an ML model on the fly
behind the scenes
and then ranking the attributes
that have the biggest influence on the variable we've picked
such as a returning customer.
Further, I can use the visual to automatically
see the largest segments of my data
to find and share even more insights.
And now, finally,
I want to show one more new AI capability.
To do so, I'm gonna switch over and look
at the trends for our new and returning customers.
Let's click on the anomaly page.
While we do have an automatic anomaly detection,
that's not actually the feature I want to show you.
Instead, for this presentation we're creating,
which we're showing to my execs,
this day-to-day spiky set of data is way too complicated.
I'd rather show a rolling average that helps smooth
and summarize the data,
but I don't currently have a calculation set up to do
a rolling average in the data set.
So I'm gonna switch over to Power BI desktop
to show you how we've infused Azure Open AI models
to make it super easy to add complex calculations.
I'm just gonna click on the suggested measure button
and type in the calculation I'm looking for;
rolling 30 day average of the number of customers.
Now by leveraging Azure Open AI large language models,
we can automatically generate the calculation needed
to do a rolling 30 day average.
I can review the output really quickly
and go ahead and add it to my model.
Now I can easily drag and drop the measure
to my add it to my report to get the view
I'm looking for to using my presentation.
Creating complex calculations like this can be a challenge
for many users,
but by leveraging Azure Open AI,
we're making it so that a much wider audience of analysts
can get work done more quickly
with co-pilot like experiences.
I'm gonna make a few more changes to my report page
to get it ready to share
and now publish it back to Power BI.
And now I can use it in my Power BI presentation
or share it directly through Microsoft Teams
or SharePoint or even embed it within a Power app.
As you've seen, power BI
is not only seamlessly bringing data and insights
into the key experiences where teams get work done,
like PowerPoint,
but we're also infusing AI to make it incredibly easy
to explore data, find insights,
and generate content to share with your team.
- [Speaker #2] Power Apps is the best choice
to efficiently build modern,
high quality intelligent applications.
Our latest improvements help makers
to build apps more efficiently,
admins to have more visibility and control
and end users to enjoy more beautiful
and modern experiences.
I'll show you how our latest innovations
help companies like Lumen through the perspective of Taylor,
an experience maker who was recently hired in the company.
As Taylor opens the power apps maker portal,
they are greeted by this very useful onboarding message.
This is because Lumen is using manage environments.
Providing their admins more visibility
and more control with less effort.
In this case, the admin has configured
an onboarding message with instructions for new makers,
but this is just one of the many settings
that an admin can control.
After reading the message,
Taylor notices the simplified navigation in the power apps
maker portal that brings the most used options
front and center into a cleaner
and more efficient experience.
If you're thinking, this is great,
but what I use more often is not there anymore,
you don't need to worry, we got you.
First, everything is still available.
Second and even better,
the left navigation is configurable
so you can make it your own
and have the things that you care the most about
always one click away.
In this case, I will have cards to
the left navigation because I use them a lot.
Taylor's boss, like everyone else,
is excited about the experiences and productivity gains that
chat-based generative AI technologies bring to users.
So they ask Taylor to add chat-based AI
to their damage claims application.
Taylor could quickly
create a new application by telling
the maker co-pilot what they need in everyday words.
However, the application already exists,
so they need to just find it and edit it.
And as Taylor edits the application,
the first thing that they notice
is that the app looks fantastic
because it uses the preview of fluent controls for Canvas.
Taylor finds the data analyzer control
and adds it to the claims list screen.
As soon as the control is added,
it can be connected to a data source.
Taylor just made the app intelligent
in a few seconds without writing any code.
So now, Taylor runs the app and it looks great.
The controls have all the sophisticated interactions
and designs from fluent
and now users can ask questions
about the list of claims
and get intelligent responses
supported by power apps end user copilot.
To try this, I'll ask what is the region
with more claims?
To which I get an answer,
from the copilot.
I can ask follow up questions like,
how many of those incidents are urgent?
Users of Taylor's app can now enjoy
a co-pilot that will help them work with their data,
and in case that you were wondering,
the fluent improvements are not only for Canvas,
we also have a fluent preview for model apps,
which has been modernized using
the latest and greatest fluent components.
Coming back to the app,
now that Taylor is done with the changes,
they are ready to deploy the app
into a production environment.
With the general availability of pipelines,
deploying from one environment
to another has never been easier.
After the pipeline has been configured in the admin console,
all Taylor needs to do
is just click a button
and their application will be deployed
from a development environment
to a production environment, like professionals do.
We just saw how our latest innovations
help improve the experience of makers
and users and admins.
From helping getting started
to supporting advanced makers
to create and deploy beautiful AI infused apps,
we have improvements for everyone
and the best, all of these
improvements are available for you to try today.
- [Speaker #3] Our automate desktop now
has open AI functionalities embedded.
From the text with GPT function,
there are multiple templates readily available for me to get
started across different scenarios.
In this example,
we are using the text with GPT function to summarize large
amount of customer feedback into a paragraph.
Firstly,
I validate using the test feedback from our customers
to ensure that the text with GPT function
is able to summarize the feedback accurately.
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Once I'm happy with that,
I would want to ask
the user via display message to approve
if the summarized feedback is valid or invalid.
Once I've got the information on whether
it's approved or not,
I make a decision to say if it's approved,
I want to include this information
in a web-based browser
and if not, I would stop the flow.
I now test the flow.
First with a scenario where the approval is given
and we can see the web-based form
is filled up accurately.
And then I retest the function
now with the disapproval
to not continue with the customer feedback.
And you can see
the feedback is not approved.
I'm now happy with the desktop flow
and therefore I save it.
Going back to the cloud flow,
I can now replace the text with GPT function
that is currently there
and use purely the desktop flow card
to be able to run the whole end-to-end
chat GPT function,
including updating the web-based form
vendor approval of the customer feedback is given.
In this case,
I'm using the output from the CSV table
as an input into the function.
Now, how do I monitor my desktop flows?
Desktop flows activity
or DFA for short is a new feature
in PowerAutomate that we've just launched in G8.
DFA enables users a cockpit view of the health
of all desktop flows and machine
that the user has access to.
There are multiple pivots available in DFA
and we are currently in the last runs pivot,
which shows all desktop floor runs within the last 28 days,
including the number of successful
and filled runs and trend over time.
The errors pivot shows all the errors that have occurred in
my desktop flows.
I can filter on a specific error type
to see which desktop flow
it's occurring on and on which machine.
This helps me to troubleshoot problematic flows
and or machines.
The machines pivot.
I can see the state of all my machines
and machine groups in a glance.
This enables me to identify any issues
in my automation infrastructure.
The current runs pivot shows,
all desktop floors that are currently running or in queue.
Going back to the last run pivot,
I want to zoom in on a recent desktop floor run
that I've created earlier.
I'm now able to cross launch directly from DFA
to the floor run details page,
which now shows me all the activities that I've done as part
of the desktop flow,
including the text with GPT functionality.
Thank you.
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