Invite Your Boss to the Business Track at MongoNYC

Meghan Gill
May 23, 2013 | Updated: May 22, 2015
#mongodb days

MongoDB Days have traditionally been focused on the developer community, with lots of technical talks on application design, deployment best practices, and ops war stories. MongoNYC will carry on the tradition of including many deep technical sessions, with talks from the 10gen staff on the latest features in 2.4, as well as presentations from MongoDB community members on their experiences deploying MongoDB in real-world scenarios.

But this year at MongoNYC, we’re introducing a new track aimed at IT managers, directors, and C-level executives who aren’t knee-deep in code. The business track will include case studies from 10gen customers with a focus on the business benefits of using MongoDB, such as reduced cost, new revenue streams and competitive advantaged. We’ll look at the steps enterprises take to adopt NoSQL and open-source technologies, and how you can learn from their experiences.

Here are some of the talks included on the business track at MongoDB NYC:

  • Telefonica explains how it reduced development time by over 80% from its previous Oracle implementation, building a rich, globally available user data management system.

  • ADP describes how it built a mobile app in just a few months to let customers view payroll and benefits information on their devices of choice, differentiating ADP from stale on-premise solutions.

  • Criteo shows how it supported 200,000% growth over five years and global expansion to 7 continents migrating away from SQL Server to MongoDB for its core business, improving online shopping by bringing the performance of search to display advertisers.

  • And more.

So if you’re a developer or DBA who loves MongoDB, but you’ve only been able to use it for small or side projects, consider inviting your boss to MongoNYC this year. Or, attend the business track and return to the office as an advocate for the business advantages of MongoDB in your enterprise.

For more information on MongoDB NYC or to register, please visit http://www.10gen.com/events/mongonyc-2013. Tomorrow is your last chance to register at the early bird rate, which is only $75. Looking forward to seeing you there.

← Previous

New Geo Features in MongoDB 2.4

Motivation Geometric processing as a field of study has many applications, and has resulted in lots of research, and powerful tools. Many modern web applications have location based components, and require a data storage engines capable of managing geometric information. Typically this requires the introduction of an additional storage engine into your infrastructure, which can be a time consuming and expensive operation. MongoDB has a set of geometric storage and search features . The MongoDB 2.4 release brought several improvements to MongoDB’s existing geo capabilities and the introduction of the 2dsphere index . The primary conceptual difference (though there are also many functional differences) between the 2d and 2dsphere indexes, is the type of coordinate system that they consider. Planar coordinate systems are useful for certain applications, and can serve as a simplifying approximation of spherical coordinates. As you consider larger geometries, or consider geometries near the meridians and poles however, the requirement to use proper spherical coordinates becomes important. In addition to this major conceptional difference, there are also significant functional differences, which are outlined in some depth in the Geospatial Indexes and Queries section of the MongoDB documentation. This post will discuss the new features that have been added in the 2.4 release. What’s New Storing non-point geometries Unlike the 2d index, which only allowed the storage of points, the 2dsphere index allows the storage and querying of points, lines, and polygons. To support the storage of different geometries, instead of introducing a proprietary format, MongoDB conforms to the GeoJSON standard. GeoJSON is a collaborative community project that produced a specification for encoding entities in JSON. It has garnered significant support, including the OpenLayers project , PostGIS , and has growing language support for python and ruby . Here are a few simple examples of GeoJSON embedded documents: A BSON Document with a GeoJSON Point embedded in the geo field: { geo: { type: “Point”, coordinates: [100.0, 0.0] } } A BSON Document with a GeoJSON LineString embedded in the geo field: { geo: { type: “LineString”, coordinates: [ [100.0, 0.0], [101.0, 1.0] ] } } A BSON Document with a GeoJSON Polygon embedded in the geo field: { geo: { type: “Polygon”, coordinates: [ [ [100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0] ] ] } } Note: A GeoJSON Polygon’s coordinates are an array of arrays of point specifications. Each array of point specifications should have the same starting and ending point to form a closed loop. The first array of point specifications defines the polygon’s exterior geometry, and each subsequent array of point specifications defines a “hole” in the polygon. Polygons should be non self-intersecting, and holes should be fully contained by the polygon. Inclusion searches on a sphere The new $geoWithin operator, which takes a Polygon geometry as a specifier, returns any geometries of any type that are fully contained within the polygon. It will work well without any index, but must look at every document in the collection to do so. Intersecting geometries on a sphere The new $geoIntersects operator, which takes any geometry as a specifier, returns any geometries that have a non-empty intersection with the specifier. $geoIntersects also works well without an index, and must also look at each document in the collection. Better support for compound indexes The 2d index can only be used in a compound index if 1. it is the first field, 2. there are exactly two fields in the compound index, and 3. if the second field isn’t a 2d index. 2dsphere indexes aren’t limited in this way, which allows us to pre-filter based on a non-geo field - which is often more efficient. Consider the following queries: Find me Hot Dog Stands in New York state i.e. use a compound index: (business_type, location). Find me geometries in New York state that are Hot Dog stands i.e. use the compound index: (location, business_type) The first query will be much more efficient than the second, because business_type is a simple text field, and greatly reduces the set of geometries to search. Additionally, we can have multiple 2dsphere indexes in the same compound index. This allows queries like: “Find routes with a start location within 50 miles from JFK, and an end location within 100 miles of YYC”. How it Works Everything starts when you insert a geometry into a 2dsphere index. We use the open source s2  C++ library  from google to select a minimal set of cells that fully cover a geometry. This set of grid cells is called a covering, and the size of the cells is dynamic (between 500m and 100km on a side) based upon the size of the polygon being covered. fig 3 - A very low granularity covering of the entire United Kingdom fig 4 - A fairly granular covering of the A4 around Trafalgar Square.  Each cell in these coverings is now added to a standard B-tree index, with a key that is easily calculable by the location on surface of the sphere - more granular(smaller) cells will have the same prefix as a larger cell that occupies the same area of the surface of the sphere. Intersection & Within searches Finding geometries that may be intersecting or within a search polygon becomes as easy as generating a covering for the search specifier, and for each cell in that covering, query the B-tree for any geometries that interact with these cells. Once the list of possibly interacting geometries has been retrieved from the index, each geometry in checked in turn to see if it should be included in the result set. Near searches The near search provided by the $near operator is implemented by doing $within searches on concentrically growing donuts (circular polygons with with circular holes).   We encourage user feedback and testing on these new Geo features and are excited to see what the community builds. Map images ⓒ  OpenStreetMap  contributors, licensed under the Creative  Commons Attribution-ShareAlike 2.0  license (CC-BY-SA).  Map data ⓒ  OpenStreetMap  contributors, licensed under the  Open Data Commons Open Database License  (ODbL).

May 21, 2013
Next →

Sales Development Series: Meet the North America Account Development Team

Sales Development is a crucial part of the Sales organization at MongoDB. Our Sales Development function is broken down into Sales Development Representatives (SDRs), who qualify and validate inbound opportunities from both existing and prospective customers, and Account Development Representatives (ADRs), who support outbound opportunities by planning and executing pipeline generation strategies. Both of these roles offer an excellent path to kickstarting your career in sales at MongoDB. In this blog post, you’ll learn more about our North American outbound team, which is divided into territories covering North America West, North America Central, New York City and the Mid-Atlantic, and New England, East Canada, and the South East. Hear from Regional Manager Jordan Gregory and a few Account Development Representatives about the ADR role and how MongoDB’s sales culture enables employees to grow and succeed in their career. An overview of Account Development in North America Jordan Gregory , Regional Manager of Sales Development for New England, East Canada, and the South East Account Development at MongoDB is crucial to the success of our sales organization, being the first point of contact with all of our prospective customers. We partner with our incredibly talented Enterprise Account Executives to find new business opportunities within some of the largest and most complex organizations in the world across a broad range of industries (financial institutions, video games, telecommunications, insurance - you name it!). The Account Development team culture is one of extreme ownership. It’s about controlling what we can control, building off of each other’s strengths, enjoying working together, and holding ourselves and each other accountable for growing and failing forward every day. If you work hard, you play hard, and that culminates in a lot of fun with this incredible group! MongoDB has a growth-focused culture. Our management and Sales leadership team take learning and development seriously, and the most successful individuals on the Sales team are those who are committed to growing and learning in their role. MongoDB is an open-source data platform company, and I firmly believe that if you can sell an open-source data platform, you can sell anything. This is one of the most challenging places to sell and because of that, and the focus on growth and development, I’ve seen countless people (including myself) take their careers to new heights. The hardest part of sales is prospecting, and it’s something we train our ADRs on extensively. You’ll learn how to identify your Ideal Customer Profile, execute deep discovery and qualification, and progress deals forward to Qualified Pipeline. You’ll also go through our Sales Bootcamp and on-the-job training. Another product of the ADR program is the massive impact we have on revenue which allows folks to build their internal brand and make lifelong connections. On top of that, we have structured upskill programs to set our ADRs up for success in the next role that they’re pursuing internally, whether that's as a Cloud Account Executive, an Associate Account Executive, or other non-direct sales roles like Customer Success and Field Marketing. We’ve also had internal promotions from the Sales Development org to Sales Enablement. At MongoDB, there is a lot of mobility to progress your career in the direction you want, and you’ll be truly valued as a person rather than an employee number or a revenue target. Hear from some team members Andrew Brownlee , Account Development Representative for New York City I joined MongoDB because it seemed like a great place to start my journey to being an Enterprise Sales Executive in the software industry. The people here have a winning mentality and operate as a team when faced with a challenge. The products are world-class and we invest heavily in R&D. MongoDB also has a process called BDR to CRO that’s geared towards developing and promoting sales talent year over year. The most exciting part about working here is the opportunity ahead. To be successful at MongoDB takes conviction, drive, and curiosity. You have to be firm in your opinion that our technology can transform an organization for the best. You must have the drive to push when it's easy, and when it's hard. The best ADRs are focused on being effective with their activity day-to-day and aren't dissuaded by how easy or hard that particular quarter is. Curiosity will help you grow in your career. It’ll also help you get the respect you need amongst your stakeholders. Maria Dorsey , Account Development Representative for North America Central I joined MongoDB because I was looking for a challenging yet rewarding start to my software sales career. It was clear to me throughout the MongoDB interview process that there is a huge emphasis on growth and development which is exactly what I was looking for. During my onboarding, I received a lot of support from my team. Although learning the MongoDB value proposition, products, and sales process can seem overwhelming, my team set aside time to ensure I was ramping up successfully. My manager also took the time to listen to my concerns, talk through tech fundamentals, walk through use cases I was unfamiliar with, and was an ally that I could depend on. What makes me stay at MongoDB is the opportunity for growth, the culture of the Sales Development organization, and the collaboration with enterprise reps and management. I’ve been extremely lucky to learn from and work alongside Enterprise Account Executives, Regional Directors, and my Regional Vice President who all truly care about my growth and success. The biggest thing that makes someone successful as an ADR is their willingness and eagerness to learn. MongoDB doesn’t necessarily care if you come from a software sales background (some of the best ADRs have not), but rather your ability and eagerness to learn the tech, sales process, and stakeholder management. These characteristics are a great foundation for building a long successful career at MongoDB. Vlad Pak , Account Development Representative for North America West I joined MongoDB because I wanted to challenge myself and gain experience working in enterprise sales. MongoDB is an incredible company that offers many opportunities for personal, professional, and financial growth, but the thing that keeps me happy here is the culture. I am surrounded by driven and intelligent teammates and leadership that cares about my success. It's great to be supported from an employee-first perspective. I think the two key traits that make someone successful on my team and in my role are proactiveness and curiosity. Many of our team members are proactively sharing insights, collaborating, and facilitating engagement with each other which benefits us all and drives us to be the best ADRs we can be. Curiosity is the bread and butter of any successful sales professional and will directly impact the quantity and quality of the meetings we set, helping us attain our quotas! I am looking forward to growing my career with MongoDB in a closing role and taking on the challenge of owning my own sales cycle. It’s exciting to work for a company that is leading the charge in digital transformation and changing the way enterprises approach technological innovation. It has been a great learning experience so far, and I can’t wait to see how the organization will grow and evolve along with my career! Interested in joining the sales team at MongoDB? We have several open roles on our team and would love for you to transform your career with us!

September 27, 2021