MongoDB On The Road - Node+JS Interactive
October 10-12, 2018 brought 1,000 developers to Vancouver, BC, Canada for the Node+JS Interactive 2018 conference. Put on by The Linux Foundation, the conference provided talks for two days followed by a day of workshops. MongoDB was a proud Bronze Sponsor of the event. This allowed us to have a booth in the Sponsor Showcase Hall along with having a presence at the Career Fair event.
MongoDB had a great presence at Node+JS Interactive 2018. Aydrian Howard and I from the Developer Advocacy team were on hand to answer questions. Thomas Cirri was there from our Recruiting team. By the way, we’re hiring! Dan Aprahamian from our Node.js Driver team was there along with Gregg Brewster from MongoDB University.
The Sponsor Showcase Hall was filled most of the day with people learning about all aspects of the Node.js ecosystem. The MongoDB booth was busy handing out swag and answering questions about MongoDB Atlas, MongoDB Stitch, MongoDB Charts, along with many other subjects and topics.
Node+JS Interactive 2018 Sessions
The schedule of session talks brought a wide variety of topics and speakers to Vancouver. Irina Shestak from MongoDB gave a great talk on HTTP/2 walking through the connection process one frame at a time and giving special attention to how Node.js implements this protocol.
Jenna Zeigen’s talk From Parentheses to Perception: How Your Code Becomes Someone Else's Reality provided some wonderful information on the path from an idea in a developer’s mind, to pixels on the screen.
There were many other talks from great speakers such as Tierney Cyren from NodeSource, Joe Karlsson from Best Buy, and Adam Baldwin from npm, just to name a few.
Node+JS Interactive 2018 Venue
Node+JS Interactive was hosted by the Vancouver Convention Center - West. Located in the West End area of Vancouver, it overlooks Vancouver Harbor and sits adjacent to the Olympic Cauldron at Jack Poole Plaza.
Vancouver Harbour is not only a busy cargo port bringing in goods for Western Canada, but it is also a heavily trafficked float plane area with seaplanes taking off and landing throughout the day. It was quite a site to be in a conference center and looking out over the harbor’s spectacular scenery and seeing the seaplanes land, taxi, and take off in the crisp and clear fall air.
MongoDB’s BI Connector the Smart Connector for Business Intelligence
September 25, 2018
In today's world, data is being produced and stored all around us. Businesses leverage this data to provide insights into what users and devices are doing. MongoDB is a great way to store your data. From the flexible data model and dynamic schema, it allows for data to be stored in rich, multi-dimensional documents. But, most Business Intelligence tools, such as Tableau, Qlik, and Microsoft Excel, need things in a tabular format. This is where MongoDB's Connector for BI (BI Connector) shines.
MongoDB BI Connector
The BI Connector allows for the use of MongoDB as a data source for SQL based business intelligence and analytics platforms. These tools allow for the creation of dashboards and data visualization reports on your data. Leveraging them allows you to extract hidden insights in your data. This allows for more insights into how your customers are using your products.
The MongoDB Connector for BI is a tool for your data toolbox which acts as a translation layer between the database and the reporting tool. The BI Connector itself stores no data. It serves as a bridge between your MongoDB data and the business intelligence tools.
The BI Connector bridges the tooling gap from local, on-premise, or hosted instances of MongoDB. If you are using MongoDB Atlas and are on an M10 or above cluster, there's an integrated built-in option.
Why Use The BI Connector
Without the BI Connector you often need to perform an Extract, Transform, and Load (ETL) process on your data. Moving it from the "source of truth" in your database to a data lake. With MongoDB and the BI Connector, this costly step can be avoided. Performing analysis on your most current data is possible. In real-time.
There are four components to a business intelligence system. The database itself, the BI Connector, an Open Database Connectivity (ODBC) data source name (DSN), and finally, the business intelligence tool itself. Let's take a look at how to connect all these pieces.
I'll be doing this example in Mac OS X, but other systems should be similar. Before I dive in, there are some system requirements you'll need:
- A MongoDB Atlas account
- Administrative access to your system
- ODBC Manager, and
- The MongoDB ODBC Driver for DSN
Instructions for loading the dataset used in the video in your Atlas cluster can be found here.
Feel free to leave a comment below if you have questions.
MongoDB On The Road - Seattle CodeCamp
September 20, 2018
Seattle CodeCamp was held in the Pigott Building on the beautiful Seattle University campus. With the scenic Puget Sound just a few blocks to the west down Madison St and Lake Washington to the east down Cherry St, Seattle CodeCamp was situated in a magnificent venue.
This year, on Saturday, September 15, 2018, 450 developers attended the event. The sponsorship hall had representatives from a few of the conference sponsors including GitHub, Flatiron School, and the College of Science and Engineering from Seattle University. There were plenty of stickers and sponsor information up for grabs along with some great representatives from the companies to talk with.
The conference sessions included over 65 sessions. One of the things I really enjoy about the CodeCamp events I’ve attended is the wide variety of speakers and session topics available. Everything from front-end to back-end topics is open game and available to learn.
And that’s just a small sample of the topics covered at this year’s Seattle Codecamp. I presented a talk on MongoDB & Node.js to a room of about 25 people. I brought with me a supply of MongoDB socks to give session attendees some swag which went over well. A large percentage of people in the room were unfamiliar with MongoDB in general and the MEAN/MERN stack specifically.
As a result, I tailored my talk to discuss the technologies themselves before showing how building an API is done with Node.js, Express.js, and MongoDB. I built an API that served up restaurants indexed by location. After building a functioning API I showed some of the features of MongoDB Compass to explore the data, perform CRUD operations, and leverage the geo-spatial data that was being stored inside MongoDB.
There were several MongoDB specific questions brought up during the session about some of the differences between the way legacy, relational databases store information and how a next generation database, such as MongoDB handles similar schema design and queries. It was a great discussion and provided a great opportunity to educate developers on the flexibility of MongoDB’s document model and the increase in development speed. You can find the project code on GitHub along with the talk slides here.
MongoDB is the easiest and fastest way to work with data. Download MongoDB Compass today and start making smarter decisions about document structure, querying, indexing, and more.
New to MongoDB Atlas — Data Explorer Now Available for All Cluster Sizes
At the recent MongoDB .local Chicago event, MongoDB CTO and Co-Founder, Eliot Horowitz made an exciting announcement about the Data Explorer feature of MongoDB Atlas. It is now available for all Atlas cluster sizes, including the free tier.
The easiest way to explore your data
What is the Data Explorer? This powerful feature allows you to query, explore, and take action on your data residing inside MongoDB Atlas (with full CRUD functionality) right from your web browser. Of course, we've thought about security; Data Explorer access and whether or not a user can modify documents is tied to her role within the Atlas Project. Actions performed via the Data Explorer are also logged in the Atlas alerting window.
Bringing this feature to the "shared" Atlas cluster sizes — the free M0s, M2s, and M5s — allows for even faster development. You can now perform actions on your data while developing your application, which is where these shared cluster sizes really shine.
Check out this short video to see the Data Explorer in action.