September 2021 Summaries

MongoDB has been ranked as one of Crain's Best Places to Work in NYC for the fifth consecutive year, ranking #29 among large companies. The company is passionate about its mission of making data easy to work with and prioritizes an inclusive culture that supports employee growth and business impact. MongoDB provides various benefits such as meditation sessions, yoga classes, fertility assistance, and a generous parental leave policy to promote employee well-being. The company also promotes diversity and inclusion through affinity groups and has supported organizations fighting for racial justice and equal opportunity. Employees praise the company's culture, citing opportunities for growth, care from leaders, and a sense of purpose in their work. MongoDB is committed to supporting employees' personal and professional development, making it a great place to work for everyone.

Cognizant's Next Gen Continuous Integrator is a UI-based tool that enables organizations to accelerate app delivery through a template-driven approach and containerization. It helps teams migrate data from legacy systems to the cloud, update applications quickly, and deliver optimal experiences to customers and end-users. The tool addresses the lack of in-house expertise and resources needed for agile CI/CD solutions by providing a flexible schema, ease of development, and rich query capabilities that support various platforms. By leveraging MongoDB's advantages, Cognizant's Next Gen Continuous Integrator offers benefits such as easier migration, quicker turn-around time, improved quality, increased savings, and portability across any platform.

Leadgence is a company that uses MongoDB to grow revenue for enterprise companies targeting small and mid-size businesses, offering smart actionable data to support sales and marketing efforts in the financial services sector. The company has evolved its products since launching, including the launch of DataSeeker, an application delivering event and change-based triggered actionable data intelligence. Leadgence chose to build with MongoDB due to its document-native approach and ease of use through MongoDB Atlas, which made it easy to spin up infrastructure as code with Terraform. As the company has scaled, it has used MongoDB as an analytics database, running online inquiries on it for instant results. The MongoDB for Startups program has been helpful in supporting Leadgence's growth, providing consulting sessions and guidance. Sergey, co-founder of Leadence, is constantly learning new lessons as a company, including the importance of solving problems in simple ways and staying up-to-date with market trends through networking with professionals in entrepreneurship and technical spaces.

MongoDB Atlas for Government has achieved the "FedRAMP In-process" designation, reflecting its progress toward a modern data platform for the US Government. The platform is widely used across federal agencies and allows governments to build and iterate faster with a modern database-as-a-service platform. It offers features such as automated backups, private link, KMS, federated authentication, Atlas Search, and more, while also supporting client-side field level encryption. MongoDB Atlas for Government is available through AWS GovCloud or the AWS marketplace, catering to government customers and companies selling to the US Government. This designation is a significant milestone in the platform's journey toward FedRAMP authorization.

Wipro's ModerniZ tool, powered by MongoDB, offers a practical and incremental approach to modernizing mainframe data and workloads into cloud-hosted microservices. This helps enterprises increase agility, lower the risk of aging legacy skills, and reduce total cost of ownership. By offloading inquiry services data from the mainframe, businesses can improve response time, scale volume handling, and reduce mainframe TCO. The ModerniZ platform uses Command Query Responsibility Segregation (CQRS) to separate read and write operations, making it easier to optimize performance and create a new model that can grow vertically and horizontally. MongoDB's document model and extensive capabilities make it an ideal choice for housing the offloaded "read data model." The joint offering aims to alleviate risks associated with big bang mainframe exit strategies, particularly in financial services, insurance, and retail sectors.

At MongoDB, the Enterprise Sales team is growing rapidly and conducting a rigorous interview process to find the right candidates. The typical interview process includes three interviews, a sales profile assessment, and "The Challenge" final interview, which aims to meet as many people on the team as possible and expose candidates to the company's broader culture. To prepare for the interview, it is recommended to treat the recruitment process like a sales cycle, including preparation, qualification, and closing, and be aware of the three Whys: Why MongoDB?, Why you?, and Why now?. The candidate should research the executive leadership team, product differentiators, and the company's sales process, highlighting their own skills and experiences in areas such as coachingability, drive, street smarts, ability to build pipeline, and champion building. The candidate should also be prepared to discuss their current role, their reasons for leaving, and their confidence in joining MongoDB at this time.

You're preparing for a Customer Success interview at MongoDB, a company that invests in its team members and supports their passions and interests. To prepare, review the job description and research the company's products, services, mission, history, and culture to understand if it's a good fit for you. Come prepared with questions to ask your interviewer(s), as this is an opportunity to interview them too. Research MongoDB's current product offerings, customer use cases, and managed service offering to get a feel for how the company uses its products in the field. Familiarize yourself with noSQL databases and practice explaining common interview questions related to stakeholder relationships, technical situations, prioritization, and adaptability. Prepare specific examples of your experiences in these areas to share with your interviewer. The interview process includes several stages, including a recruiter interview, hiring manager interviews, peer role plays, data assignment challenges, customer success manager interviews, and mock onboarding challenges. Each stage assesses different aspects of your skills and experience. By preparing thoroughly for each stage, you can demonstrate your qualifications and interest in the Customer Success role at MongoDB.

Drowning in Data: Why It's Time to End the Healthcare Data Lake` discusses the challenges faced by the healthcare industry in modernizing their analytics data warehouses and data lakes. The traditional approach of physically moving all data into a single warehouse or lake, followed by updates to improve performance, has proven costly and inefficient. New technologies like Hadoop have failed to solve these issues and have instead introduced new challenges. The article proposes an alternative approach called the operational data layer (ODL), which can help mitigate legacy system issues without replacing them. An ODL strategy uses a flexible document-based database to build new features, summarize, analyze, and respond to data events in real-time, making it an ideal solution for healthcare organizations looking to deliver real-time data and analytics at the speed of agile software delivery teams.

Four Tips for Writing and Applying with Your Engineering Resume | MongoDB Blog` At MongoDB, they encourage creative and passionate engineers who want to make an impact. To make their engineering resume stand out, they suggest keeping it concise, focusing on core technologies and tools, using standard fonts and formats, being intentional about the roles applied for, and highlighting what makes them unique through a summary or interests section.

MongoDB and Palisade Compliance are helping companies transform their architecture and shift to a cloud-first world, moving away from legacy RDBMS like Oracle. To achieve this, organizations need to understand their business and technical requirements, decipher their Oracle contracts and compliance positions to maximize cost reduction initiatives, and mobilize internal momentum and traction to make the move. MongoDB can help with understanding requirements and finding the right partner, while Palisade Compliance assists with managing Oracle licenses and reducing costs. A modern data platform like MongoDB is essential for accelerating and simplifying software development, featuring a flexible data model that aligns with how developers think and code, as well as providing auto-scaling, multi-node replication, and in-place real-time analytics. By partnering with a technical expert like MongoDB and leveraging Palisade Compliance's expertise in Oracle licensing and contracts, organizations can build confidence and momentum to make the move away from legacy RDBMS.

With the latest release of the MongoDB Charts SDK, users can now apply highlights to their charts using the new highlight capability. This allows for emphasizing and deemphasizing data points with query operators, enabling a richer interactive experience for customers. Highlights can be used to show user interactions or attract attention to specific parts of the chart, such as profit or unfilled orders. The `setHighlight` method is now available in the chart object, which uses MQL queries to decide what gets highlighted. This feature supports most chart types and will continue to expand. Developers can use the highlighting sandbox and examples to get started with applying highlights to their charts.

Amazon Managed Grafana is a fully managed service that makes it easy to visualize and analyze operational data at scale, allowing organizations to analyze data stored in MongoDB Atlas without having to provision servers or configure software. The MongoDB Grafana plug-in enables users to query MongoDB with Amazon Managed Grafana, simply selecting MongoDB as a data source and connecting using an Atlas connection string and proper authentication credentials. Users can then write queries in the query editor and visualize their data through Amazon Managed Grafana, illustrating how certain fields change over time. By connecting MongoDB to Amazon Managed Grafana, users can easily analyze MongoDB data alongside other data sources, affording a singular point of reference for all important data in an application.