Dashed is a data exploration platform designed to be visual, intuitive and interactive.

[this project used to be named Panoramix]

Dashed's main goal is to make it easy to slice, dice and visualize data. It empowers its user to perform analytics at the speed of thought.

Dashed provides:

• A quick way to intuitively visualize datasets
• Create and share interactive dashboards
• A rich set of visualizations to analyze your data, as well as a flexible way to extend the capabilities
• An extensible, high granularity security model allowing intricate rules on who can access which features, and integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuiler)
• A simple semantic layer, allowing to control how data sources are displayed in the UI, by defining which fields should show up in which dropdown and which aggregation and function (metrics) are made available to the user
• Deep integration with Druid allows for Dashed to stay blazing fast while slicing and dicing large, realtime datasets

Dashed was originally designed on to of Druid.io, but quickly broadened its scope to support other databases through the use of SqlAlchemy, a Python ORM that is compatible with most common databases.

From their website at http://druid.io

Druid is an open-source analytics data store designed for business intelligence (OLAP) queries on event data. Druid provides low latency (real-time) data ingestion, flexible data exploration, and fast data aggregation. Existing Druid deployments have scaled to trillions of events and petabytes of data. Druid is best used to power analytic dashboards and applications.

Dashed is currently only tested using Python 2.7.*. Python 3 support is on the roadmap, Python 2.6 won't be supported.

Follow these few simple steps to install Dashed.

# Install dashed
pip install dashed

# Create an admin user
fabmanager create-admin --app dashed

# Initialize the database
dashed db upgrade

# Create default roles and permissions
dashed init

# Load some data to play with
dashed load_examples

# Start the development web server
dashed runserver -d

After installation, you should be able to point your browser to the right hostname:port http://localhost:8088, login using the credential you entered while creating the admin account, and navigate to Menu -> Admin -> Refresh Metadata. This action should bring in all of your datasources for Dashed to be aware of, and they should show up in Menu -> Datasources, from where you can start playing with your data!

most common databases.

(See in the documentation) [http://mistercrunch.github.io/panoramix-docs/installation.html]

From their website at http://druid.io

Druid is an open-source analytics data store designed for business intelligence (OLAP) queries on event data. Druid provides low latency (real-time) data ingestion, flexible data exploration, and fast data aggregation. Existing Druid deployments have scaled to trillions of events and petabytes of data. Druid is best used to power analytic dashboards and applications.

• [Dashed Google Group] (https://groups.google.com/forum/#!forum/airbnb_dashed)
• Gitter (live chat) Channel

Dashed would not be possible without these great frameworks / libs

• Flask App Builder - Allowing us to focus on building the app quickly while getting the foundation for free
• The Flask ecosystem - Simply amazing. So much Plug, easy play.
• NVD3 - One of the best charting library out there
• Much more, check out the requirements.txt file!

Interested in contributing? Casual hacking? Check out Contributing.MD