What We're Reading
Here's this week's roundup of news from the MongoDB community.
Gazzang Advice from a Big Data Pro
I Learn As I Go Along MongoDB Aggregating Fractals
MongoHQ MongoDB Data Management
MongoHQ Q&A with Gild
The MongoDB Blog Visualizing Performance Metrics of a Sharded Cluster with One MMS Chart
The MongoDB Blog The 2013 FinTech Hackathon
The MongoDB Blog Meet Dan Pasette: VP of Engineering for the Server Team
OpenLife The Answer to Last Week’s MongoDB Aggregation Challenge
Reverb Partitioning MongoDB Data on the Fly
Vlad Mihalcea NoSQL is Not Just About Big Data
Vlad Mihalcea MongoDB Facts: Lightning Fast Aggregation
Meet Stacy Ferranti: Campus Recruiting and University Relations Manager
We're excited to introduce you to Stacy Ferranti, our Campus Recruiting and University Relations Manager. What is your role at MongoDB? I manage our Campus Recruiting and University Relations program. I recruit current students and recent graduates to join our summer internship or new grad program. I focus mostly on software engineers and tech recruits. Once the interns and new grads arrive, I manage the summer program and new grad rotational program. I liken what I do to the NFL draft: bringing up college kids to the pros. Where were you before MongoDB? Why did you choose to come to MongoDB? I studied International Politics in school and I thought I’d move to DC and change the world. I took a 180 and moved to Hong Kong instead to live abroad and be young and reckless for a while. After coming back to the states I kind of fell into recruiting. Right before I came to MongoDB I worked for Gap Inc. in their Talent Management Department. When I decided to move to New York, I contacted my network here. A few people I knew at Sequoia Capital referred me to MongoDB. The company had about 30 people at the time and the office was small and a bit intimidating. But after my first interview something sparked; I knew this company was going to be huge and I had to be here no matter what. How did you learn how to pitch MongoDB to students and developers after starting? I actually learned a ton from our co-founder and CTO Eliot Horowitz; he took the time to teach me what a database was and how ours was different. I persistently had lunch with our engineers and asked them to tell me about what they did. But I also spent a lot of time researching on Google, and following the philosophy of “fake it ‘til you make it”. What’s your hometown? I’m from a small mountain town in Southern California called Lake Arrowhead, but since I spent so much time in San Francisco, I consider that my second home. Bike or public transportation to work? I take the subway and brave the crowds at both Grand Central and Times Square. I have to put on my game face for every commute: every woman for herself! I have a bad habit of taking cabs when there is any hint of inclement weather. I hate the rain. What’s a typical day (or week) for you? Fall and spring are very busy since I could be at any number of college campuses across the country; I travel a lot during the recruiting seasons. When I’m not travelling, a typical day would start at 6am when I get up to work out. I go back home for a cup of coffee and start checking my emails. Inevitably I get lost in my emails and don’t get to the office until much later than I had planned. Once I’m in the office, I try to practice time blocking. The morning consists of reading student emails (which always seem to be sent between 12 and 4 am) reviewing resumes, and contacting candidates. I’m usually on the phone from 1 to 6 pm or later. In the summers, I spend the entire day running the internship program and planning for the upcoming fall. What’s the most interesting thing you’ve seen on a resume? I’ve seen some pretty interesting stuff on resumes. A lot of chess champions, and body-builders, people doing standup comedy, many people claiming to be connoisseurs of various types of food. What do you love most about MongoDB? I love the collaboration, transparency, and shared interests and passions I have with my co-workers. MongoDB is creating disruptive technology by developers for developers—it’s not social networking or a fleeting technology that no one will have heard of 10 years from now—which is really important to me. And the people I work with are absolutely amazing. What’s the most challenging aspect of your job? In a world of instant gratification, shiny things, and over the top perks at tech companies it’s so challenging to convey what actually matters in life to college students. What’s one of the most rewarding experiences you’ve had working here so far? I love seeing our summer interns turn into full time employees. When they get shout outs in our company-wide emails for the work they do, it puts me on cloud nine and makes all the long hours and travel beyond worth it! What’s your MongoDB kitchen snack weakness? I’m absolutely addicted to Oreos. Can’t stop, won’t stop! Name one secret skill you have, unrelated to work. I am surprisingly good at identifying and imitating American regional accents. My favorite is Minnesotan. Kindle or book? What’s your favorite book? Books. I’m old school. I love just about anything from John Steinbeck or Annie Proulx. But my favorite book is The Story of Edgar Sawtelle. I really enjoy stories about humans being humans, especially when the ending isn’t particularly happy. Describe your perfect weekend. When I romanticize New York, it’s perpetually fall (when I think New York is most beautiful). I’d start with Friday night dinner at my neighborhood Italian spot with nothing to do the next morning. Then I’d get up early and have coffee at home, leave the house with no agenda and get lost in the city. I’d spend the day discovering new neighborhoods, new restaurants, etc. And if it’s football season, it’s football Sunday (49ers all the way!) What’s your favorite cocktail? I’m always in search of the perfect Bloody Mary or Michelada. What ‘s your dream honeymoon? (Stacy is getting married in July!) Ideally somewhere warm and tropical where I would have nothing to do but enjoy the company of my new husband! If you're interested in joining the MongoDB Team there are a number of open positions available in Engineering, Sales, Marketing, and Business Development. To learn more about open roles at MongoDB, please visit the MongoDB Careers Page.
Accelerating to T+1 - Have You Got the Speed and Agility Required to Meet the Deadline?
On May 28, 2024, the Securities and Exchange Commission (SEC) will implement a move to a T+1 settlement for standard securities trades , shortening the settlement period from 2 business days after the trade date to one business day. The change aims to address market volatility and reduce credit and settlement risk. The shortened T+1 settlement cycle can potentially decrease market risks, but most firms' current back-office operations cannot handle this change. This is due to several challenges with existing systems, including: Manual processes will be under pressure due to the shortened settlement cycle Batch data processing will not be feasible To prepare for T+1, firms should take urgent action to address these challenges: Automate manual processes to streamline them and improve operational efficiency Event-based real-time processing should replace batch processing for faster settlement In this blog, we will explore how MongoDB can be leveraged to accelerate manual process automation and replace batch processes to enable faster settlement. What is a T+1 and T+2 settlement? T+1 settlement refers to the practice of settling transactions executed before 4:30pm on the following trading day. For example, if a transaction is executed on Monday before 4:30 pm, the settlement will occur on Tuesday. This settlement process involves the transfer of securities and/or funds from the seller's account to the buyer's account. This contrasts with the T+2 settlement, where trades are settled two trading days after the trade date. According to SEC Chair Gary Gensler , “T+1 is designed to benefit investors and reduce the credit, market, and liquidity risks in securities transactions faced by market participants.” Overcoming T+1 transition challenges with MongoDB: Two unique solutions 1. The multi-cloud developer data platform accelerates manual process automation Legacy settlement systems may involve manual intervention for various tasks, including manual matching of trades, manual input of settlement instructions, allocation emails to brokers, reconciliation of trade and settlement details, and manual processing of paper-based documents. These manual processes can be time-consuming and prone to errors. MongoDB (Figure 1 below) can help accelerate developer productivity in several ways: Easy to use: MongoDB is designed to be easy to use, which can reduce the learning curve for developers who are new to the database. Flexible data model: Allows developers to store data in a way that makes sense for their application. This can help accelerate development by reducing the need for complex data transformations or ORM mapping. Scalability: MongoDB is highly scalable , which means it can handle large volumes of trade data and support high levels of concurrency. Rich query language: Allows developers to perform complex queries without writing much code. MongoDB's Apache Lucene-based search can also help screen large volumes of data against sanctions and watch lists in real-time. Figure 1: MongoDB's developer data platform Discover the developer productivity calculator . Developers spend 42% of their work week on maintenance and technical debt. How much does this cost your organization? Calculate how much you can save by working with MongoDB. 2. An operational trade store to replace slow batch processing Back-office technology teams face numerous challenges when consolidating transaction data due to the complexity of legacy batch ETL and integration jobs. Legacy databases have long been the industry standard but are not optimal for post-trade management due to limitations such as rigid schema, difficulty in horizontal scaling, and slow performance. For T+1 settlement, it is crucial to have real-time availability of consolidated positions across assets, geographies, and business lines. It is important to note that the end of the batch cycle will not meet this requirement. As a solution, MongoDB customers use an operational trade data store (ODS) to overcome these challenges for real-time data sharing. By using an ODS, financial firms can improve their operational efficiency by consolidating transaction data in real-time. This allows them to streamline their back-office operations, reduce the complexity of ETL and integration processes, and avoid the limitations of relational databases. As a result, firms can make faster, more informed decisions and gain a competitive edge in the market. Using MongoDB (Figure 2 below), trade desk data is copied into an ODS in real-time through change data capture (CDC), creating a centralized trade store that acts as a live source for downstream trade settlement and compliance systems. This enables faster settlement times, improves data quality and accuracy, and supports full transactionality. As the ODS evolves, it becomes a "system of record/golden source" for many back office and middle office applications, and powers AI/ML-based real-time fraud prevention applications and settlement risk failure systems. Figure 2: Centralized Trade Data Store (ODS) Managing trade settlement risk failure is critical in driving efficiency across the entire securities market ecosystem. Luckily, MongoDB integration capabilities (Figure 3 below) with modern AI and ML platforms enable banks to develop AI/ML models that make managing potential trade settlement fails much more efficient from a cost, time, and quality perspective. Additionally, predictive analytics allow firms to project availability and demand and optimize inventories for lending and borrowing. Figure 3: Event-driven application for real time monitoring Summary Financial institutions face significant challenges in reducing settlement duration from two business days (T+2) to one (T+1), particularly when it comes to addressing the existing back-office issues. However, it's crucial for them to achieve this goal within a year as required by the SEC. This blog highlights how MongoDB's developer data platform can help financial institutions automate manual processes and adopt a best practice approach to replace batch processes with a real-time data store repository (ODS). With the help of MongoDB's developer data platform and best practices, financial institutions can achieve operational excellence and meet the SEC's T+1 settlement deadline on May 28, 2024. In the event of T+0 settlement cycles becoming a reality, institutions with the most flexible data platform will be better equipped to adjust. Top banks in the industry are already adopting MongoDB's developer data platform to modernize their infrastructure, leading to reduced time-to-market, lower total cost of ownership, and improved developer productivity. Looking to learn more about how you can modernize or what MongoDB can do for you? Zero downtime migrations using MongoDB’s flexible schema Accelerate your digital transformation with these 5 Phases of Banking Modernization Reduce time-to-market for your customer lifecycle management applications MongoDB’s financial services hub