STEPHANIE WONG: Hey, it's Stephanie.
And today, I'm super excited to talk about sharing
and monetizing data using APIs.
Let's get into it.
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In this modern digital world powered by smart IoT devices,
hundreds of petabytes of data are generated every second
as consumers increasingly prefer online shopping,
mobile banking, telehealth, and other digital services.
On the other hand, organizations are
looking to harness the power of this data,
using tools like Google Cloud BigQuery
to deliver personalized experiences,
make data-driven business decisions,
improve organizational efficiency,
and unlock new revenue.
However, there are several challenges
in putting data into action.
These include data residing in silos,
security concerns over sharing proprietary data,
and the complexity of monetizing data consumption.
This is where APIs can help.
By packaging data as API products,
you can create a standardized way
to aggregate data across systems,
securely share data with other teams and external partners,
and create rate plans and bill for the consumption of data.
Let's take a closer look.
In this demo, we are going to use Apigee to easily
consume and monetize a large set of weather data from BigQuery.
So the first step is to use Apigee to create
an API, which pulls this data.
If you look at this API proxy setup,
we configured it to fetch all the necessary weather data
from a BigQuery backend target.
Let's take a closer look at the API proxy.
You'll see that there are many things
a proxy can add while fetching the information requested.
It can secure the API, do rate limiting,
caching, and get a token to authenticate the BigQuery API.
And on the return flow, you can reformat the BigQuery response
so that it's easier to consume.
After creating the Apigee proxy, the next step
is to create an API product.
For this demo, I created a weather API product.
And you can see that this product uses the same weather
API that we built earlier.
This product also has a rate plan associated with it
for monetization purposes.
It helps bill the user for every API call
made to fetch weather data from BigQuery.
When you click on this rate plan,
you can see the pricing details of $0.12
for every API call made.
Now let's switch roles and take a look
at how an API consumer would sign up to use this weather API
and get billed for it.
The first step would be to visit the Apigee developer portal
and view all the APIs.
Then I can go over to Buy APIs, pick a subscription that best
suits my requirements, and review the pricing information.
The next step would be to create a client app that
uses the Weather API product.
I created an app called weather-client.
When you click on it, you can see the Consumer Key, which
identifies this client app.
Now that I have an authorized app to access the API,
let's test this API and see how I get billed for consumption.
For that, let's go to the API documentation
and click on the Weather API.
Here, you can see the endpoint, required parameters,
body of the API, and other details.
Let's test out this API.
You can enter the city and API key that has been granted,
and execute it to fetch all the weather stations near Santa
Monica from BigQuery.
Let's take one of these weather stations
and make another API call over here to get the temperature.
Let's enter the same API key, choose a year,
enter one of the weather stations
that we got from the previous API call, and click Execute.
This gives me the temperature of every day in 2015
at Santa Monica from BigQuery.
Since I made two API calls, let's
now see how much I was billed for this consumption.
Let's go to the Analytics view and look at the custom report
I created.
This report shows the overall traffic.
If I chose a specific developer, you
can see that two API calls were made
and were billed $0.24, since each call was
configured for $0.12.
In summary, Apigee makes it simple and easy
to package your business data as APIs.
This allows you to securely share
with other teams and partners, as well as monetize
for additional revenue.
Now it's your turn to try it out and get
started by following the links in the description below.
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