Get Started in No-Code App Development with Unqork and MongoDB

MongoDB
October 7, 2021 | Updated: June 3, 2022

Classic application development can be a long haul process. Even using Agile methodologies, teams of developers still work to build, test, and launch applications in a series of sprints, using many of the same programming languages and approaches as they have for years.

That was until the concept of low and no-code app development arrived. Aiming to cut development cycles and empower non-developers, no-code in particular is gaining traction as a go-to-market strategy for modern apps. No-code is an alternative to traditional application and software development processes, allowing apps to be built through a simplified, interactive UI, rather than writing code from scratch.

While the concept of no-code tools has been around for a while - from Visual Basic to WYSIWYG web editors like Wix and “super spreadsheets” like Airtable - newer no-code-based application development platforms take the concept a step further, dramatically simplifying the application development process itself.

In the booming world of no-code, one company stands above the rest, Unqork. Unqork invented the first completely visual, no-code application platform to help enterprises build custom software faster, with higher quality and lower costs than traditional approaches––all without a single line of code.

And with Unqork freeing organizations from the traditional constraints of developing with code, it was only natural that the pioneer of no-code application development partnered with MongoDB to also free them from the constraints of database design and management.

Syncing Unqork with MongoDB Atlas

Building out a new no-code application with Unqork is efficient and simple. From the database side of things, MongoDB has everything that a business needs with functionality to store, manage, and analyze data. MongoDB and Unqork are each functional and powerful in their own capacity, but when used together, an organization can truly improve and innovate their application development experience.

Diagram of Unqork syncing with MongoDB — *Fig 1: Unqork syncs seamlessly with MongoDB Atlas*

Use Case Example: Mortgage Approval Application

Large financial institutions have many separate functions and applications in use. A typical large bank will employ many different applications and microservices, all of which rely on many different data sources. This can quickly lead to complexity for their software infrastructure. The bank must make intelligent choices for their app development to stay lean and agile and not add unnecessary complexity.

In this example, a bank decides to build out a new mortgage approval application as part of their loan origination infrastructure; an otherwise complex process that requires a variety of data, from bank information to customer background information, and data enrichment. The bank wants to build a portal where customers can log on, request a certain amount of money, and the application can decide whether or not they want to approve the mortgage quickly. In theory, the application objective is simple, however it needs to pull on the greater customer database for data collection and analysis.

Let's break down the simple steps of this integration process.

Step 1: Create an Unqork application

Since Unqork is a no-code application, it’s simple to drag and drop objects into the format wanted. For this example, text fields were used for users to input their data into the application. This app is a mortgage approval application, so we wanted to look at the customer’s information as well as how much money they are looking to borrow.

Screenshot of creating a Unqork application — *Fig 2: Creating an Unqork application*

The creation of the application is a single screen that allows users to define the overall concept and functions of the mortgage approval application, and manage the influx and outflow of data.

Screenshot of Unqork application for mortgae approval — *Fig 3: Screenshot of our Unqork application for mortgae approval*

In Figure 3 we see elements and functions simply on the left side of the screen, representing the available functions, that can be dragged into the user screen and put into context with their execution.

Step 2: Configuring MongoDB Atlas and Realm

While MongoDB is the underlying data platform for Unqork, it is unlikely that all customer data in a large, multi-department organization like a bank would always reside in Unqork. Therefore the bank's “Client 360 data layer” - held in a separate MongoDB Atlas instance - needs to be connected to Unqork.

Given this, the next step is to get your MongoDB cluster ready to connect to the new Unqork-built mortgage approval application. MongoDB Atlas enables this connection via MongoDB Realm’s HTTP Endpoints (previously named Webhooks).

MongoDB Realm is a set of application development services that makes it simple to build best-in-class apps across mobile and the web, like HTTP endpoints. Other services include edge-to-cloud data sync, instant GraphQL API, triggers, and functions.

To work with MongoDB Realm’s HTTP endpoints, you must first create a Realm app – the central backend instance for your mobile or web application. You can easily create an app using MongoDB’s web GUI, as shown in the figure below.

Screenshot of MongoDB Realm interfacel — *Fig 4: Creating an application in MongoDB Realm*

Step 3: Connect MongoDB Atlas to Unqork application

Finally, in order to realize the benefits of both MongoDB Atlas and Unqork, we need to connect them to each other. As previously stated, this is achieved through MongoDB Realm’s HTTP endpoints. Both MongoDB Realm and Unqork have easy to use interfaces when it comes to sending requests over HTTPS with services like endpoints, and all we need to do is write the logic for the endpoint itself. By using MongoDB Realm functions we are able to access MongoDB Atlas data easily and connect to third party applications simply and with minimal code.

To connect the Unqork application to MongoDB Atlas, we’ll first need to set up our endpoints in MongoDB Realm. This provides us with an endpoint URL that we can use from Unqork. We can also define our HTTP endpoint serverless function here to send and receive data with Unqork.

This is done from within Unqork. We navigate to “Administrator Access” and create a connection. Using the HTTP URL from Realm, we can create a connection within Unqork. Going back to our Unqork application, we can then create a plugin and use the integration that we created before. We have to fill in the correct information pertaining to the webhook, but once done, we’ll have our connection.

To learn more about migrating to MongoDB Atlas and what that means for accelerated development, connect with the MongoDB team here. To request a demo of Unqork or learn more about development acceleration with their No-code approach, connect here.

MongoDB & Unqork: No-Code Together

While MongoDB and Unqork individually are powerful platforms, when deployed in tandem they provide a powerful solution to accelerate development.

MongoDB Atlas gives us the ability to run our database on multiple clouds through the same service,” said Unqork Founder and CEO, Gary Hoberman. “With Atlas, we have the freedom from cloud vendor lock-in—each client can choose where they are the most comfortable hosting their data.”

Together, development is automated and optimized, allowing for more time on innovation and less time on maintenance and upkeep. For businesses, the no-code movement has many benefits, including freeing them to focus on differentiating projects, like developing apps that customers actually want, rather than maintaining lines of code and waiting for teams of developers to build the traditional way.

The value together brings:

Accelerated time-to-market: With Unqork, enterprise applications can be developed three times faster. Teams are empowered to deploy quickly without the traditional code-based approach. Meanwhile, MongoDB, by design, is developer and DevOps friendly with its flexible use and automation. Together, time-to-market is decreased as resources can be spread more evenly across teams.
Reduced TCO: With Unqork, the development process requires fewer resources providing three times cost savings versus Total Cost of Ownership (TCO) with a code/low-code-based approach. Meanwhile, MongoDB’s cost of managing and running a database is already taken care of and remains highly available even throughout system updates.
Engaged employees: Unqork provides a collaborative platform that frees technology from high-volume development and management tasks so a team can do the best work of their careers. MongoDB allows developers to work in their desired programming language, with idiomatic drivers, flexible data models and intuitive building.
Unlocked innovation: Because projects can get ramped up quickly with lower costs by using Unqork, the cost of innovation and experimentation is greatly mitigated. Similarly in MongoDB, creating and developing a database can be done at speeds that drastically beat traditional relational databases.

Both Unqork and MongoDB work with large organizations across some of the world’s most regulated and complex sectors, making security yet another key reason the two became partners.

“One of the big things that drew us to MongoDB Atlas over the other DBaaS providers was the security features,” Hoberman added. "When we partner up with a client, we take over and support their most critical processes and data assets."

Unqork keeps all data encrypted in-transit and at-rest throughout the entire platform and Atlas allows each Unqork customer to have their own MongoDB instance with their own development and production environments.

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Honoring Hispanic Heritage Month

We’re honoring Hispanic Heritage Month (September 15 to October 15) in a few ways here at MongoDB! First, hear from three MongoDB employees about their own experiences and what this month means to them. Then, keep scrolling for a Spotify playlist, reading list, and movie list curated by members of our affinity group the Underrepresented People of Color Network (TUPOC). Alicia Raymond , Director, HR Business Partner (Core & Cloud), New York City At 18 years old, and without knowing a word of English, my mother left behind her entire family in Chile to come to the United States. This was in 1973, shortly before the dictator Augusto Pinochet came into power. The following years in Chile were tumultuous and my mother, who was now married to a U.S. military member, relocated frequently. Over time, she lost contact with her family in Chile. Years later, I was a college student at the University of North Carolina at Chapel Hill on a Morehead-Cain scholarship. The scholarship allowed me to take part in various summer activities, including a summer of studying abroad. Chile was on the list of countries where I could study, so I jumped at the opportunity to go there and find my family. As soon as the plane touched down, I began searching for traces of my family members. This was before the prevalence of social media, so I spent a lot of time sifting through phone books. Finally, I was able to locate a phone number for my mother’s younger sister, Esther, but I didn’t call her right away. I was anxious about how I would fit in with my Chilean relatives. My identity as Latina had always felt a bit nebulous — a common feeling among multiracial, multicultural people and second-generation immigrants. I was Spanglish-speaking and white-passing, and I had not grown up among a Latinx community in the U.S. At the time, I struggled to feel like part of the Latinx community, but I also felt a deep obligation not to abandon the complex mix of identities I inherited from my mother — a mix we are still learning about today. Until recently, she didn’t know she was almost half Indigenous American — a detail her parents hid to improve their chances of integrating into the middle class of Chilean society. Alicia with her mother and aunts from Chile in New York City Eventually, I worked up the courage to make the call. After a few rings of the phone, someone picked up on the other end. I confirmed that it was Esther and then, in broken Spanish, I explained who I was and that I was in Chile. Esther’s excitement melted away all of my concerns. We scheduled a time to meet in person that week, and we have remained in contact ever since. After re-establishing and maintaining contact with my Chilean family, my bonds with my Chilean heritage strengthened. Although my cultural identity still feels complicated, within that complexity lies an incredible blessing. It has given me the opportunity to navigate multiple worlds and be shaped by varied perspectives and communities. That’s not to imply that those identities always meshed in a frictionless way — my father’s parents almost disowned him for marrying my Latina mother — but even that friction helped expand my view of the world. In a career context, this has allowed me to be highly adaptable to new circumstances, adept at perspective-taking, and flexible enough in my own beliefs to understand others’ viewpoints. Those skills are essential for my role as an HR Business Partner, where the issues I face often involve multiple stakeholders, rarely have one right answer, and require a big dollop of creative problem-solving. I am eternally grateful for the multifaceted lens my cultural background has provided me. Alicia's mother as a child, outside the house she grew up in Gustavo Chavez , Senior Solutions Architect, Austin Hispanic Heritage Month is not just a month, it’s a lifestyle! I’m originally from a small town in Mexico and was raised all over the state of Chihuahua. Growing up, I was always fascinated by airplanes and technology, and when I reached high school I had the opportunity to start learning computer programming. My friend’s father owned a payroll-processing company, and he started teaching RPG and COBOL on an IBM System 34 (yeah, I know, I’m dating myself) during the afternoons, so I would go there two or three times a week. This is where my passion for computers and technology really grew and led me to pursue a degree in computer science. After graduating, I began working at a local startup doing offshore work for a mainframe application performance-monitoring company located in Santa Monica, California. The company, Candle Corp, then offered me the opportunity to work for them in the U.S., so my wife and I packed our things in a U-Haul and drove 900 miles west to Los Angeles! IBM acquired Candle Corp in the mid-2000s, which led me to Austin, Texas. After a few years, I had the opportunity to join MongoDB. Diversity is celebrated here, and we all work together toward a common goal while having fun along the way. In my role as a Senior Solutions Architect, I support the LATAM Corporate Sales organization and help align MongoDB technology with customer needs and business goals. My children were born in Los Angeles, where, as an immigrant, I started thinking about my role as a parent in preserving Hispanic language and culture for the next generation. Luckily, it wasn’t too difficult given our location. The shared history between Mexico and the U.S. provides the perfect canvas to paint a picture of blended colors and influences from other places. This is apparent all across Texas and the southwest of our country. The food, architecture, names, battles, and social struggle through the years help build the foundation of what it means to be of Hispanic descent in the United States. We are embedded in the fabric of the region and country, and that is what we aim to share with everybody — our common bonds instead of our differences. Today, as the proud father of two young adults attending university, I can honestly say the job is not done. We still have other generations to share our culture and heritage with. I hope we can ensure that future generations are proud of being Hispanic and proud of the contributions made by members of the Hispanic community to the United States. Gustavo and his family Camilo Velez-Gordon , Field Marketing Specialist, New York City In 2003, my mom and I hopped on a one-way flight from Colombia to Newark International Airport with four suitcases and a lot of unknowns. As a 7-year-old with minimal knowledge of the English language, I had no idea what it meant for me or my future, and I was terrified. My family and I quickly settled in northern New Jersey, and I learned English in less than a year thanks to cartoons and shows such as Rocket Power and Drake and Josh. Throughout my upbringing, I learned that two things will always be true: Family is and always will be an important part of my life, and in the United States you are in control of your destiny, which may not be the case elsewhere. The older I get, the more significance Hispanic Heritage Month has in my life. This may be due to a deeper understanding of the importance of culture and my background. The month is a great opportunity to reflect on my journey to where I am today, and also a good time to educate the people around me about what it is like to be Latino in today’s America. The tech industry has always been fascinating to me, but, while in school, a career in tech always seemed like a far-fetched goal. Through my network, I was fortunate enough to secure a marketing internship for an ad-tech firm while finishing my senior year as a business student at Montclair State University. Once I got my foot in the door, I was determined to take full advantage of the opportunity. To this day, my main takeaway from the process of getting into tech is that mastering the skill of networking will open many doors in your career. As I approach my two-year anniversary at MongoDB, I frequently look back on my journey to where I am today, and I can’t help but smile. The terrified 7-year-old from 17 years ago came a long way. At MongoDB, I continue to grow, evolve, and learn. During my tenure, I have met incredible people, achieved many milestones, and launched multiple global programs that have had a positive impact on the business. I am so proud of how far my family and I have come, and I could not be more excited for what is to come for MongoDB. Camilo and his family Celebrate the Hispanic and Latinx community's contributions to music, literature, and film Spotify Reading list Title Author The House on Mango Street Sandra Cisneros I Am Not Your Perfect Mexican Daughter Erika L. Sanchez The Brief Wondrous Life of Oscar Wao Junot Diaz Dominicana: A Novel Angie Cruz War Against All Puerto Ricans: Revolution and Terror in America's Colony Nelson A. Denis Latinx Superheroes in Mainstream Comics Frederick Luis Aldama Empire's Workshop: Latin America, the United States, and the Rise of the New Imperialism Greg Grandin Borderlands/La Frontera: The New Mestiza Gloria Anzaldúa The Borders of Dominicanidad Lorgia Garcia-Peña The Battle for Paradise: Puerto Rico Takes on the Disaster Capitalists Naomi Klein The Arawak: The History and Legacy of the Indigenous Natives in South America and the Caribbean Charles River Editors The Indian Chronicles José Barreiro Eva Luna Isabel Allende The Bronx Evelyn Gonzalez Barrio Dreams: Puerto Ricans, Latinos, and the Neoliberal City Arlene Dávila Bodega Dreams Ernesto Quiñonez The Eagle's Throne Carlos Fuentes The Poet X Elizabeth Acevedo When I Was Puerto Rican: A Memoir

October 4, 2021

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The Converged AI and Application Datastore for Insurance

In the inherently information-driven insurance industry, companies ingest, analyze, and process massive amounts of data, requiring extensive decision-making. To manage this, they rely on a myriad of technologies and IT support staff to keep operations running smoothly but often lack effectiveness due to their outdated nature. Artificial intelligence (AI) holds great promise for insurers by streamlining processes, enhancing decision-making, and improving customer experiences with significantly less time, resources, and staff compared with traditional IT systems. The convergence of AI and innovative application datastores is transforming how insurers work with data. In this post, we’ll look at how these elements are reshaping the insurance industry and offering greater potential for AI-powered applications, with MongoDB at the heart of the converged AI and application datastore. Scenario planning and flexible data layers One of the primary concerns for IT leaders and decision-makers in the insurance industry is making smart technology investments. The goal is to consolidate existing technology portfolios, which often include a variety of systems like SQL Server, Oracle, and IBM IMS. Consolidation helps reduce inventory and prepare for the future. But what does future-proofing really look like? Scenario planning is an effective strategy for future-proofing. This involves imagining different plausible futures and investing in the common elements that remain beneficial across all scenarios. For insurance companies, a crucial common thread is the data layer. By making data easier to work with, companies can ensure that their technology investments remain valuable regardless of how future scenarios unfold. MongoDB’s flexible developer data platform offers a distinct architectural advantage by making data easier to work with, regardless of the cloud vendor or AI application in use. This flexibility is vital for preparing for disruptive future scenarios, whether they involve regulatory changes, market shifts, or technological advancements. Watch now: The Converged AI and Application Datastore: How API's, AI & Data are Reshaping Insurance The role of AI and data in insurance Generative AI is revolutionizing the insurance sector, offering new ways to manage and utilize data. According to Celent's 2023 Technology Insight and Strategy Survey, 33% of companies across different industries have AI projects in planning, 29% in development, and 19% in production (shown in Figure 1 below). This indicates a significant shift towards AI-driven solutions by insurers actively experimenting with gen AI. Figure 1: Celent Technology Insight and Strategy Survey 2023 However, there's tension between maintaining existing enterprise systems and innovating with AI. Insurance companies must balance keeping the lights on with investing in AI to meet the expectations of boards and stakeholders. The solution lies in integrating AI in a way that enhances operational efficiency without overwhelming existing systems. However, data challenges need to be addressed to achieve this, specifically around access to data. According to a Workday Global Survey , only 4% of respondents said their data is fully accessible, and 59% say their enterprise data is somewhat or completely siloed. Without a solid data foundation, insurers will struggle to achieve the benefits they are looking for from AI. Data architectures and unstructured data When adopting advanced technologies like AI and ML, which require data as the foundation, organizations often grapple with the challenge of integrating these innovations into legacy systems due to their inflexibility and resistance to modification. A robust data architecture is essential for future-proofing and consolidating technology investments. Insurance companies often deal with a vast amount of unstructured data, such as claim images and videos, which can be challenging to manage. By leveraging AI, specifically through vector search and large language models, companies can efficiently process and analyze this data. MongoDB is ideal for managing unstructured data due to its flexible, JSON-like document model, which accommodates a wide variety of data types and structures without requiring a predefined schema. Additionally, MongoDB’s flexibility enables insurers to integrate seamlessly with various technologies, making it a versatile and powerful solution for unstructured data management. For example, consider an insurance adjuster assessing damage from claim photos. Traditionally, this would require manually reviewing each image. With AI, the photos can be converted into vector embeddings and matched against a database of similar claims, drastically speeding up the process. This not only improves efficiency but also enhances the accuracy of assessments. The converged AI and application datastore with MongoDB Building a single view of data across various systems is a game-changer for the insurance industry. Data warehouses and data lakes have long provided single views of customer and claim data, but they often rely on historical data, which may be outdated. The next step is integrating real-time data with these views to make them more dynamic and actionable. A versatile database platform plays a crucial role in this integration. By consolidating data into a single, easily accessible view, insurance companies can ensure that various personas, from underwriters to data scientists, can interact with the data effectively. This integration allows for more responsive and informed decision-making, which is crucial for staying competitive in a rapidly evolving market. This can be achieved with a converged AI and application datastore, as shown in Figure 2 below. This is where operational data, analytics insights, and unstructured data become operationally ready for the applications that leverage AI. Figure 2: Converged AI and application datastore reference architecture The convergence of AI, data, and application datastores is reshaping the insurance industry. By making smart technology investments, leveraging AI to manage unstructured data, and building robust data architectures, insurance companies can future-proof their operations and embrace innovation. A versatile and flexible data platform provides the foundation for these advancements, enabling companies to make their data more accessible, actionable, and valuable. The MongoDB Atlas developer data platform puts powerful AI and analytics capabilities directly in the hands of developers and offers the capabilities to enrich applications by consolidating, ingesting, and acting on any data type instantly. Because MongoDB serves as the operational data store (ODS)—with its flexible document model—insurers can efficiently handle large volumes of data in real-time. By integrating MongoDB with AI/ML platforms, insurers can develop models trained on the most accurate and up-to-date data, thereby addressing the critical need for adaptability and agility in the face of evolving technologies. With built-in security controls across all data, whether managed in a customer environment or through MongoDB Atlas, a fully managed cloud service, MongoDB ensures robust security with features such as authentication (single sign-on and multi-factor authentication), role-based access controls, and comprehensive data encryption. These security measures act as a safeguard for sensitive data, mitigating the risk of unauthorized access from external parties and providing organizations with the confidence to embrace AI and ML technologies. If you would like to learn more about the convergence of AI and application datastores, visit the following resources: Video: The Converged AI and Application Datastore: How API's, AI & Data are Reshaping Insurance Paper: Innovation in Insurance with Artificial Intelligence The MongoDB Solutions Library is curated with tailored solutions to help developers kick-start their projects

July 18, 2024