Today, we are expanding the capabilities of the Google Visualization API by enabling developers to display data from any data source connected to the web (any database, Excel spreadsheet, etc.), not just from Google Spreadsheets. From pivot tables and heat graphs to motion charts and timelines, the Google Visualization Gallery holds a growing set of 40+ visualizations that appeal to a multitude of businesses.
As companies open their platforms, we expect to see increased integration of data and services across clouds, benefiting the enterprise community.
DashboardZone earlier released a wordpress plugin to monitor and track Blogging Goals and this plugin uses Google Visualization API
We hope to see more reporting and dashboarding tools leveraging the APIs to create “Dashboards on the Cloud” (…just a lame effort to keep up with the folks on cloud terminology,jargon,etc)
But How do you connect to any Data Source?
According to the development team
The essence of our announcement today is that we documented our protocol, or
‘opened’ it up. We now enable both from a terms of service and from a
practical perspective to create Visualization compliant data sources.
The results is that anybody can expose their data in this format, and so
visualize their data with visualizations supporting the API.
That said, you still need to actually expose the data to be visualized in
There are two ways you can do this:
– You can create a data source. This means that you will have a url that
can accept HTTP requests and return the JSON response as described
If you take this approach, you can send requests to this data source by
pointing to this url from the Query object. See more
– You can use the JSON notation in the DataTable object constructor. This
way, you generate the page on the server, including the data table to be
visualized on the page. You don’t have to follow the full protocol of
request and response, but only follow the JSON notation of DataTable,
Note that in this case there is no way to specify this as a data source url,
and so it can’t be used in gadgets, for example.
The main point is that other than the Python library implementation, we have
exposed the protocol to enable you to connect your data sources (as
described in the two options above) but we have not provided actual
implementations of these. While we do intend to make connecting to generally
available data sources in the future easier, it is up to the community (you)
to do the implementations for data sources (be it general ones, like an
implementation for SQL data for example, or specific ones for your own
If you want, you can share these implementations with the community (you can
freely share them or you can also create a business model around that if you
wish). We intend to make it easy to find general implementations of data
sources by creating a gallery similar to the visualization and gadget
gallery. If you’re so fast as to create such an implementation before we
place the data sources gallery on the docs, feel free to shoot us a note on