It’s critical to select a forward-looking approach to how you organize, use, and enrich your data in the cloud. Modern data repositories have made it easy to store your unstructured data, but getting insights from that data has often been challenging and involve batch ETL processes, data pipelines, and so on. In this session, we show you how to build complex queries to draw valuable insights from data directly in MongoDB and then visualize it using MongoDB Charts—a tool built to natively process rich, nested JSON documents.

1. Ben Perlmutter, Senior Solutions Architect
MongoDB
Visualize Your Cloud Data Strategy:
MongoDB Atlas and Charts

2. 2
Options for Visualizing Unstructured Data
Custom Code + Charting
Libraries
ETL + 3rd Party BI
Tools
BI Connector Tools

3. 3
Introducing MongoDB Charts
The fastest way to build
visualizations over your
MongoDB data
Built for the MongoDB
document model
Visualize live data
From on-prem or Atlas DBs

4. 4
Options for Getting Set Up
On-Premises
You want to visualize data from MongoDB
Community Server, Enterprise Server or
Atlas
You want to keep all data within your
private network
You want control over the infrastructure
hosting Charts
As a Managed Service
You want to visualize data only from
MongoDB Atlas
You want to spend your time visualizing
data, not managing servers and software
You want to immediately get access to the
latest Charts features

5. Launching Charts on Atlas

6. 6
Charts Basic Concepts
A data source is a reference to a MongoDB collection or view that contains data you want
to visualize.
A chart is a visualization of data from a single data source.
A dashboard is a collection of charts which you manage as a unit (name, layout, sharing).

7. Charts Basic Workflow

8. 8
Charting Capabilities
Common chart types
Aggregation functions
Filtering
Binning
Sorting

9. Charting Capabilities

10. 10
Document Model Support
Type handling
Polymorphic collections
Nested documents
Array reductions

11. Document Model

12. 12
Sharing and Permissions
All users log onto Charts with their own account
• In Charts on Atlas, users sign in with their Atlas account
• In Charts On-Premises, users can be managed by anyone with the UserAdmin role
Any user can add a data source or a dashboard
• The user who creates it is the owner
• The owner can choose to share with nobody, specific people or everybody

13. Sharing and Permissions

14. 14
Getting MongoDB Charts on Atlas
Sign in/up for Atlas: https://cloud.mongodb.com
Create a Project (or use an existing one)
Create a Cluster (or use an existing one)
Add users to your Project
Activate Charts in the project
Note that each Charts instance can only see Atlas clusters in the same project
Charts Beta is available at no cost

15. 15
Getting MongoDB Charts On-Premises
Download and install instructions @ http://mongodb.com/charts
Charts runs as a Docker container on a server of your choice
• Supported on any OS that runs Docker CE or EE (Linux, MacOS, Windows)
• Can be a physical server, cloud VM or even a laptop
Charts requires a MongoDB instance to run
• For storing metadata about users, data sources and dashboards
• Can be any MongoDB instance in your organization (including Atlas)
• Not included in the Charts Docker container
Charts Beta is available at no cost

16. 16
Feature Roadmap
Planned features include:
• External embedding
• Geospatial charts
• Filtering enhancements
• Interactive dashboards
• Data preparation
… Tell us what else you want to see!
The development, release, and timing of any
features or functionality described for our
products remains at our sole discretion. This
information is merely intended to outline our
general product direction and it should not be
relied on in making a purchasing decision nor is
this a commitment, promise or legal obligation
to deliver any material, code, or functionality.

17. 17
Questions, Feedback, Requests, Bugs?
Find me at MongoDB.Local
Contact me later
• benp@mongodb.com
• @ben_perlmutter
Send us a message or feature suggestion from any page in the Charts app

18. Thank You!