Building something interesting with MongoDB? Is your application leveraging MongoDB to addresses an important business need? Did you create something that wasn’t before possible?
We want to hear from you. Apply for the MongoDB Innovation Award, an annual award that recognizes organizations and individuals who create groundbreaking applications.
Innovation Award winners receive:
- A MongoDB Innovation Award
- Recognition at MongoDB World, June 20-21 in Chicago
- Photograph with MongoDB President and CEO, Dev Ittycheria and CTO, Eliot Horowitz
- MongoDB Atlas credits
All finalists will also get two passes to MongoDB World and an invitation to the VIP party.
Each year, we receive hundreds of nominations across dozens of industries. Previous winners include the startups and Fortune 500 enterprises, and companies like Facebook, Expedia, x.ai, Amadeus, and more.
Apply or nominate someone else today! In your submission, explain what the application does, how it leverages MongoDB, and the impact it has on the business. The deadline to submit is March 17.
MongoDB Certified Professional Spotlight: May Mascenik
We’re happy to introduce a new blog series interviewing MongoDB Certified Professionals . To kick off this series, we talked with May Mascenik , an IT Engineer and Project Manager based in Los Angeles at ITP . Headquartered in Japan and focused on information design, ITP utilizes new devices, creates content designed to match user activities, and researches IoT and other new fields and technologies. In 2016, May was selected as a MongoDB Diversity Scholar ; grateful for the opportunity and eager to contribute to and learn from the MongoDB community, she made the decision to become dual-certified by MongoDB as both a Developer and a DBA. We reached out to her recently to learn more about her certification story, as well as what being certified means to her. ![May Mascenik](https://webassets.mongodb.com/_com_assets/cms/may-mascenik-ahe3vttz5s.jpg) Eloise Giegerich: To start, I would love to hear a little about your background, and how you got into tech. Where do you currently work, and what do you like about your role? May Mascenik: Twenty years ago, I began working as a Project Administrator in the engineering department of the Standard Communications Corporation; because I admired the engineers’ work, I pursued an electronics course. I liked it, but the engineers recommended that I move to software in order to follow the tech trend. Later, I got a job at Hitachi Software (now Hitachi Solutions) where I was able to gain significant hands-on training. I started studying and obtaining tech certificates – one certificate per year – from Microsoft, Cisco, and ISACA, among others, mostly related to projects I was working on at the time. Since 2014, I’ve been working for a company called ITP in Los Angeles as an IT Engineer/PMP. In 2016, I chose to become MongoDB certified because I desperately wanted to be fluent in the database for the specific project I was assigned. I like my role at ITP because it always offers me opportunities to learn new technology, which in turn allows me to develop and utilize new skills. EG: How did you first discover MongoDB? What projects have you used or are you in the process of using with MongoDB? MM: I took over a web/mobile app project; the app was built with Meteor and used MongoDB as the backend. I became interested in MongoDB while working on this project, and completed the M102 DBA course through MongoDB University, then M202 and all the DEV courses (M101J, M101JS, M101N, and M101P). With my new experience and knowledge, I was able to update the app that the former developer at my company had left; I became excited after this, and began to use MongoDB for other apps. EG: What other databases have you worked with? How does MongoDB compare? MM: I have worked with Microsoft SQL, Pervasive SQL, MySQL, and Oracle; all are relational databases. When it came to MongoDB, I was amazed by the flexible and dynamic data model. I’m still handling multiple relational databases and supporting the structured and predefined architecture on my current projects. However, as our business grows toward e-commerce and CMS type solutions, MongoDB’s NoSQL database is preferred because it allows us to build an application without predefining the schema, and to add any types of data to the system with different iterations. EG: What inspired you to become MongoDB certified? Why both certifications? MM: Besides the above-mentioned reason (for my 2016 certification selection, I chose MongoDB), I was fortunate enough to be awarded the 2016 MongoDB Diversity Scholarship, and decided that getting certified was one way to continue to contribute to the MongoDB community. I worked on DBA and DEV certifications together because I work in both fields at my company, and wanted to prove that I could be dual-certified. EG: What was challenging about the courses? What was rewarding? MM: Most of the courses run for seven weeks. Though you can watch the lesson videos and complete the homework at any time, the modules have strict weekly deadlines. Having a full-time job with multiple projects, I needed to take more time for work some weeks, which gave me less time to study. But in the long run, the time crunch is good! The deadlines force one to learn without delay. I felt great when I completed each course and received the certificate of course completion; I still feel like taking more MongoDB University courses. EG: Since becoming certified, what have been some of the benefits, personal or professional, that you’ve experienced? How have you applied—or how do you intend to apply—what you’ve learned to your future projects? MM: Since becoming certified, I have become more easily recognized through the MongoDB Certified Professional Finder and Advocacy Hub websites. I also now have a strong understanding of the challenges that the other certified professionals faced; because of this, I am eager to share my own experience and contribute to MongoDB alongside its other enthusiasts. Regarding current projects, I recently started looking into using MongoDB with AEM (Adobe Experience Manager), and am eager to continue my research. EG: Looking back now, can you share any advice for those studying for (or retaking) their exam(s)? Are there any specific preparation strategies you found useful? MM: First of all, for exam retakers, I’ve passed many certification exams on my first attempt, but not MongoDB’s – so if you fail, do not get discouraged! Instead, think of the Performance Report as another lesson to consider; the exam result is not an indicator of failure, but of weak points to continue to work on. For DEV, I strongly encourage hands-on practice. When you complete the weekly homework and practice, it can be helpful to type out all of the answers and try them – run the code, verify the app or web functions – on a terminal so that you can understand what MongoDB finds acceptable. And for both DBA and DEV, stick with the official exam study guide, which provides many links to the information you should absorb. If the online courses are still one version older, cover the difference by watching the What’s New in v3.4 (or vX.X in the future) video, and read the release notes to learn about the different features that have since been included. EG: To close, I would love to know what has been your greatest takeaway from your experience getting certified. Why would you encourage others to pursue certification? MM: If I can do it, so can you! In case you lose Internet connection or get disconnected from the test site for any reason during the exam, don’t panic. It happened to me once, but all of my answers were saved and I was able to resume the exam without starting from the beginning. I would strongly encourage others to pursue a MongoDB certification; my certifications have given me great confidence and recognition thanks to my listing in the Certified Professional Finder. I am happy to receive messages and invitations from people not only in the US, but from all over the world! Thanks to May for sharing her story! If you’re interested in getting professionally certified, you can learn more about the MongoDB certification process . If you’re already certified and would like to be featured in a future blog post, let us know at email@example.com .
How DataSwitch And MongoDB Atlas Can Help Modernize Your Legacy Workloads
Data modernization is here to stay, and DataSwitch and MongoDB are leading the way forward. Research strongly indicates that the future of the Database Management System (DBMS) market is in the cloud, and the ideal way to shift from an outdated, legacy DBMS to a modern, cloud-friendly data warehouse is through data modernization. There are a few key factors driving this shift. Increasingly, companies need to store and manage unstructured data in a cloud-enabled system, as opposed to a legacy DBMS which is only designed for structured data. Moreover, the amount of data generated by a business is increasing at a rate of 55% to 65% every year and the majority of it is unstructured. A modernized database that can improve data quality and availability provides tremendous benefits in performance, scalability, and cost optimization. It also provides a foundation for improving business value through informed decision-making. Additionally, cloud-enabled databases support greater agility so you can upgrade current applications and build new ones faster to meet customer demand. Gartner predicts that by 2022, 75% of all databases will be on the cloud – either by direct deployment or through data migration and modernization. But research shows that over 40% of migration projects fail. This is due to challenges such as: Inadequate knowledge of legacy applications and their data design Complexity of code and design from different legacy applications Lack of automation tools for transforming from legacy data processing to cloud-friendly data and processes It is essential to harness a strategic approach and choose the right partner for your data modernization journey. We’re here to help you do just that. Why MongoDB? MongoDB is built for modern application developers and for the cloud era. As a general purpose, document-based, distributed database, it facilitates high productivity and can handle huge volumes of data. The document database stores data in JSON-like documents and is built on a scale-out architecture that is optimal for any kind of developer who builds scalable applications through agile methodologies. Ultimately, MongoDB fosters business agility, scalability and innovation. Key MongoDB advantages include: Rich JSON Documents Powerful query language Multi-cloud data distribution Security of sensitive data Quick storage and retrieval of data Capacity for huge volumes of data and traffic Design supports greater developer productivity Extremely reliable for mission-critical workloads Architected for optimal performance and efficiency Key advantages of MongoDB Atlas , MongoDB’s hosted database as a service, include: Multi-cloud data distribution Secure for sensitive data Designed for developer productivity Reliable for mission critical workloads Built for optimal performance Managed for operational efficiency To be clear, JSON documents are the most productive way to work with data as they support nested objects and arrays as values. They also support schemas that are flexible and dynamic. MongoDB’s powerful query language enables sorting and filtering of any field, regardless of how nested it is in a document. Moreover, it provides support for aggregations as well as modern use cases including graph search, geo-based search and text search. Queries are in JSON and are easy to compose. MongoDB provides support for joins in queries. MongoDB supports two types of relationships with the ability to reference and embed. It has all the power of a relational database and much, much more. Companies of all sizes can use MongoDB as it successfully operates on a large and mature platform ecosystem. Developers enjoy a great user experience with the ability to provision MongoDB Atlas clusters and commence coding instantly. A global community of developers and consultants makes it easy to get the help you need, if and when you need it. In addition, MongoDB supports all major languages and provides enterprise-grade support. Why DataSwitch as a partner for MongoDB? Automated schema re-design, data migration & code conversion DataSwitch is a trusted partner for cost-effective, accelerated solutions for digital data transformation, migration and modernization through a modern database platform. Our no-code and low-code solutions along with cloud data expertise and unique, automated schema generation accelerates time to market. We provide end-to-end data, schema and process migration with automated replatforming and refactoring, thereby delivering: 50% faster time to market 60% reduction in total cost of delivery Assured quality with built-in best practices, guidelines and accuracy Data modernization: How “DataSwitch Migrate” helps you migrate from RDBMS to MongoDB DataSwitch Migrate (“DS Migrate”) is a no-code and low-code toolkit that leverages advanced automation to provide intuitive, predictive and self-serviceable schema redesign from a traditional RDBMS model to MongoDB’s Document Model with built-in best practices. Based on data volume, performance, and criticality, DS Migrate automatically recommends the appropriate ETTL (Extract, Transfer, Transform & Load) data migration process. DataSwitch delivers data engineering solutions and transformations in half the timeframe of the existing typical data modernization solutions. Consider these key areas: Schema redesign – construct a new framework for data management. DS Migrate provides automated data migration and transformation based on your redesigned schema, as well as no-touch code conversion from legacy data scripts to MongoDB Atlas APIs. Users can simply drag and drop the schema for redesign and the platform converts it to a document-based JSON structure by applying MongoDB modeling best practices. The platform then automatically migrates data to the new, re-designed JSON structure. It also converts the legacy database script for MongoDB. This automated, user-friendly data migration is faster than anything you’ve ever seen. Here’s a look at how the schema designer works. Refactoring – change the data structure to match the new schema. DS Migrate handles this through auto code generation for migrating the data. This is far beyond a mere lift and shift. DataSwitch takes care of refactoring and replatforming (moving from the legacy platform to MongoDB) automatically. It is a game-changing unique capability to perform all these tasks within a single platform. Security – mask and tokenize data while moving the data from on-premise to the cloud. As the data is moving to a potentially public cloud, you must keep it secure. DataSwitch’s tool has the capability to configure and apply security measures automatically while migrating the data. Data Quality – ensure that data is clean, complete, trustworthy, consistent. DataSwitch allows you to configure your own quality rules and automatically apply them during data migration. In summary: first, the DataSwitch tool automatically extracts the data from an existing database, like Oracle. It then exports the data and stores it locally before zipping and transferring it to the cloud. Next, DataSwitch transforms the data by altering the data structure to match the re-designed schema, and applying data security measures during the transform step. Lastly, DS Migrate loads the data and processes it into MongoDB in its entirety. Process Conversion Process conversion, where scripts and process logic are migrated from legacy DBMS to a modern DBMS, is made easier thanks to a high degree of automation. Minimal coding and manual intervention are required and the journey is accelerated. It involves: DML – Data Manipulation Language CRUD – typical application functionality (Create, Read, Update & Delete) Converting to the equivalent of MongoDB Atlas API Degree of automation DataSwitch provides during Migration Schema Migration Activities DS Automation Capabilities Application Data Usage Analysis 70% 3NF to NoSQL Schema Recommendation 60% Schema Re-Design Self Services 50% Predictive Data Mapping 60% Process Migration Activities DS Automation Capabilities CRUD based SQL conversion (Oracle, MySQL, SQLServer, Teradata, DB2) to MongoDB API 70% Data Migration Activities DS Automation Capabilities Migration Script Creation 90% Historical Data Migration 90% 2 Catch Load 90% DataSwitch Legacy Modernization as a Service (LMaas): Our consulting expertise combined with the DS Migrate tool allows us to harness the power of the cloud for data transformation of RDBMS legacy data systems to MongoDB. Our solution delivers legacy transformation in half the time frame through pay-per-usage. Key strengths include: ● Data Architecture Consulting ● Data Modernization Assessment and Migration Strategy ● Specialized Modernization Services DS Migrate Architecture Diagram Contact us to learn more.