- Please join us in the final video of this demo series.
In this video, we will demonstrate how
to visualize data using Amazon Managed Grafana.
Now we have deployed the station,
they are all sending data,
and we stored it in the time stream database.
Now what needs to be done?
AWS has this wonderful data visualization tool
called Grafana.
We use the Grafana tool to actually visualize
the weather data that's sent
from Joe's weather station in Tucson
and Dan's weather station in San Francisco.
Let me walk you through the process
of adding the time stream database to Grafana
as well as like how to build a dashboard quickly.
So as you can see on my screen,
you need to go to the AWS icon here,
click on data sources, and in the data sources itself,
you can select from a range of different databases.
I selected time stream.
You can see that our data source is already there,
our time stream database is already there.
It's that simple to add the data source
from the time stream to Grafana.
Now that we know how to add the data source,
let's quickly go through how to build the dashboard.
See the plus icon here, click create,
and yes, this is the default panel that you can see here.
Before jumping into that,
let me tell you quickly that Grafana has a multitude
of different widgets that you can play around with
to add as many panels or data visual tools that you want.
You can explore more around that in the AWS Grafana website.
So click on add panel.
So you see here that there is this graph,
it's like a default graph that's already been added.
What you need to do is you have to select
that data source here.
In our case, it's the Amazon time stream database
that we have selected from.
Once you've selected, it'll automatically tell you
the data, the database and everything.
What do you need to do?
Just like any other SQL database,
you just have to add the query here, show the data.
Now, in this case, I'm showing the wind speed here.
I just copied it from my clipboard
because I do not want to bore you guys with my slow typing.
As you can see, the data is already plotted here.
That's all it is.
It's that simple to actually create a dashboard.
You can add as many different widgets you want
to create a dashboard.
So just walk you through two different items,
how to create the dashboard,
how to validate time stream data to Grafana.
Now that we have gone through these two process,
let's move on to seeing the real data
that Joe and Dan has been posting them.
Moving on, let's go to the San Francisco data first,
which is Dan's weather station.
As you can see, this looks really pretty here,
and you can see all the different data points sets
that we have here, wind speed,
we also have this beautiful wind speed histogram.
It gives you the current wind speed, gust speed,
as well as the humidity factor.
So whatever data we have collected from the weather station,
you can see all those data in a very good visualization.
This is for the San Francisco data.
And let me show you the data
from Joe's weather station in Tucson.
The temperature is really high compared to San Francisco.
This is just to walk you
through the data from both the weather stations.
Just to recap, we started with our registration sensors.
We connected those through our host
and connected that to the ExpressLink module,
send data into IoT code,
set up a rule to extract that data
and write it to the time stream.
And now we have set up Grafana
to read from that time stream.
And so all of this data is live.
What we can do with Grafana
is a very impressive visualization.
It's independent from the data collection itself.
The thing to remember is when we publish two topics,
it's going nowhere unless you take it
and actually put it into a database.
So that's why the time stream is a database
just indexed over time,
and you write one line of code.
These are real devices in the field,
and we built it in less than two weeks rather than months.
Thank you for joining Dan, Joe, and myself
on the AWS ExpressLink demo series.
Have fun with AWS ExpressLink IoT module,
and make some great projects.