May 2021 Summaries

MongoDB's internship program has been a significant factor in the company's growth, with over 30% of its U.S. engineers coming from the program. The program began in 2011 and has since expanded to multiple continents and new business units. Over the past decade, MongoDB has made a concerted effort to improve and refine the program, resulting in increased success for interns and New Grads. Many former interns have gone on to become leaders within the company, with some even returning after leaving and joining again. The program's focus on providing interesting challenges and a supportive culture has been key to its success, with many interns citing the opportunity to work on meaningful projects and learn from experienced mentors as major contributors to their growth and development.

The goal of most organizations is to improve customer offerings and become more operationally efficient, streamlined and profitable, but relying on legacy systems can hinder innovation. Digital decoupling enables organizations to detach incrementally from these systems while acknowledging their critical role, allowing for a faster, less risky, and more flexible alternative. By maintaining the existing legacy system and building modern microservices around it, organizations can utilize new technologies to reduce disruption and risk while unlocking the ability to innovate new products on a rapid timescale. MongoDB's flexible data schema makes it an excellent implementation technology for digital decoupling, providing a dynamic mechanism that can flex to new data and event types on demand.

MongoDB is the technology used by Milky Way AI, a company that provides real-time visibility into product merchandising across thousands of stores. The company's flagship product, InstaShelf, uses computer vision to generate insights for retailers and brands, empowering them with valuable data on how their products are being displayed. With a tech stack consisting of MongoDB, React Native, React, Node.js, Python Flask, TensorFlow, and Pytorch, Milky Way AI has successfully deployed its product across 150 stores in several countries, including Singapore, Malaysia, and the Philippines, and aims to expand into three more countries by the end of next year. The company's use of MongoDB features such as autoscaling and triggers has provided scalability and stability, allowing for a wide range of developer pool options and flexibility in its solution.

I wrote a book called "Practical MongoDB Aggregations" to help developers, architects, data analysts, and data engineers understand how to maximize productivity and effectiveness when building aggregation pipelines in MongoDB. The book aims to demystify the MongoDB aggregation framework, which is considered shrouded in mystery for many users. I believe there was a knowledge gap that needed to be filled, and my book provides an opinionated yet informed perspective on assembling aggregation pipelines from well-documented parts. The book includes fully formed example pipelines to help put these approaches into practice, and it's available for free online.

The Infosys Media Platform is a unified framework built on MongoDB Atlas and Enterprise Advanced that facilitates creative collaboration, enables large-scale productions, and monetizes customer relationships by integrating various ecosystems involved in the media content value chain. The platform leverages MongoDB's document model to provide smart workflows, incorporate machine learning and artificial intelligence for metadata management, and deliver benefits of productivity, scalability, and agility via the cloud. With its modules such as Curation & Digitization, Custom AI, Localization, and Metadata Management and Distribution, the platform can attain capabilities like content enrichment, closed captioning, content moderation, image processing, and metadata packaging and distribution. MongoDB powers the data platform for Infosys Media Platform by providing a document model, query language, 100+ metrics and monitoring capabilities, and cloud-agnostic nature that enables seamless operation across the globe.

### Italic, a membership-based marketplace, was founded by two high school friends who dropped out of college to pursue their entrepreneurial dreams. The platform offers manufacturers the chance to sell products directly to consumers and reach a global customer base. Since its launch in 2018, the company has raised $15 million and given consumers the chance to shop unbranded quality goods at prices 80 percent lower than comparable brands would ordinarily charge. Italic operates on a subscription model, charging for a membership that grants customers access to their entire product offering, allowing them to pass savings directly to members and profit only from annual subscription fees.

MongoDB Atlas provides database infrastructure on demand, simplifying the data layer of DevOps deployments by making it simple to create, scale, and tear down databases as needed. AWS App Runner builds and deploys applications or APIs from source code or container images, handling load balancing, scaling, monitoring, and more. MongoDB Atlas integrates seamlessly with AWS App Runner applications, addressing both the application layer and data layer deployment. Developers can leverage the scalability and performance of MongoDB Atlas for their App Runner applications. The integration enables easy deployment of an app or API in a matter of minutes, providing high availability and configuration changes through simple button clicks or API calls.

Data modernization is a growing trend driven by the need for cloud-enabled systems that can handle increasing amounts of unstructured data. Companies are shifting from legacy database management systems (DBMS) to modern, cloud-friendly data warehouses, which provide improved performance, scalability, and cost optimization. However, this process is often fraught with challenges such as inadequate knowledge of legacy applications and complexity of code and design. DataSwitch and MongoDB Atlas can help overcome these hurdles by providing a strategic approach, automated schema redesign, data migration, and refactoring capabilities. With the help of DataSwitch's no-code and low-code solutions, companies can accelerate their time to market, reduce costs, and improve data quality, while harnessing the power of MongoDB's document-based database and cloud-enabled architecture.

The latest release of MongoDB Charts adds Conditional Formatting, a feature that enables chart authors to highlight important changes in their chart data based on defined rules. This feature is useful for table charts and number charts, allowing users to apply different styles to highlight key information and provide context. The article demonstrates the use of Conditional Formatting with a Formula 1 data set, showcasing how it can aid users in understanding complex data by applying simple rules to highlight important changes. Two examples are provided: Single Color Conditional Formatting and Color Scale Conditional Formatting, which demonstrate how to apply formatting rules to specific data points or ranges of values. The article concludes that Conditional Formatting has many more powerful operators than what is demonstrated here, including matching values by range, regular expression, and ranks, and invites readers to test drive the feature themselves.

Memora Health is a healthcare technology company that has built a comprehensive platform to facilitate care delivery outside the clinic. The company was founded by college roommates who were interested in improving patient communication and care in the healthcare industry. They have raised $10.5 million from leading investors and are used by more than 50 healthcare organizations across the country. Memora's platform provides a suite of modules that simplify how patients and doctors interact, including remote monitoring and messaging programs. The company has seen significant adoption of its platform during the COVID-19 pandemic as hospitals needed to build virtual waiting rooms to enforce social distancing and safety. Memora's vision is to build an operating system for care delivery, providing a platform that intelligently digitizes existing physician workflows and provides infrastructure for how clinicians reach their patients and patients are cared for outside the hospital. The company uses MongoDB as its backend database, which has helped scale its solutions due to its ease of use and scalability.

The integration between MongoDB Atlas, Google Cloud, and Databricks enables users to gain deep insights into their data and have the freedom to move and analyze it as needed. To get started, one can create a new Databricks workspace on Google Cloud and follow the instructions provided in order to set up a cluster and connect it to a MongoDB Atlas cluster. The user must define network access, add sample data, update Spark configuration with an Atlas connection string, start the Databricks cluster, install the MongoDB Spark Connector, and create a new notebook to perform analytics on the data. With this setup, users can leverage many of the services available in MongoDB Atlas, including online archiving, search, and data lake capabilities.

MDBWomen is a community of women employees at MongoDB that aims to connect, support, and empower each other. The affinity group was started by a cohort of women in the North American recruiting organization and has since grown globally to over 500 members across chapters in India, Australia, Ireland, and U.S. locations. MDBWomen organizes various initiatives, including events during Women's History Month, professional development workshops, networking opportunities, and support for working mothers and employees identifying as LGBTQIA+. The group provides a safe space for women to share experiences, build connections, and access resources, such as fertility benefits and mentorship programs. Participating in MDBWomen has had a significant impact on the lives of its members, including reducing feelings of isolation and depression, promoting self-care and support, and fostering a sense of community and empowerment. The group's global presence allows it to connect women across different regions and cultures, providing a platform for them to share their voices and experiences.

Companies such as MongoDB and Confluent have built cloud-based solutions like MongoDB Atlas and Confluent Cloud that work across all three major cloud providers, enabling developers to build modern cloud-based applications with data in motion. To get started with MongoDB Atlas and Confluent Cloud, users can register for a free trial of Confluent Cloud and create a new Kafka cluster, followed by setting up the source and sink connectors in Confluent Cloud, generating test data, configuring the sink connector, and verifying the data arrival at the sink. With fully managed solutions like MongoDB Atlas and Confluent Cloud, users can focus on solving business problems rather than spending time on infrastructure configuration and maintenance, and can leverage features like Atlas Search, Online Archive, and MongoDB Charts to further enhance their data management capabilities.

Sean Conrad, co-founder and CEO of Go, a social app focused on helping friends create plans to hang out in person, shares his experience with MongoDB as he built his startup from scratch. He started building Go during the COVID-19 pandemic, which impacted the product's development but ultimately led to its success in New Zealand and Australia. With 40,000 downloads and 500 businesses using the app, Go has raised $6.7 million in seed funding and is planning to launch in the United States. Sean credits MongoDB for being a comfortable choice due to his previous experience with it at his previous company, and praises its features such as full-text search and serverless capabilities. As a second-time founder, Sean notes that raising capital was an unexpected challenge but has been worth it for Go's ambitious plans to help people manage their friendships in person.