Efficient, Collaborative, and Browser-Based: Meet Quary

What is Quary?

Quary is an innovative analytics engineering platform that transforms how teams interact with data. Founded in 2023, this London-based start-up is pioneering the integration of the entire model-test-deploy workflow into the browser. This approach revolutionizes the way data is handled, making it more accessible, efficient, and collaborative. By eliminating the need for complex local setups and bringing the process directly to the browser, Quary enables teams to work together more seamlessly, fostering an environment where data-driven decisions can be made more swiftly and effectively.

Who are the Founders Behind Quary?

The driving forces behind Quary are Benjamin King and Louis Jordan, both of whom bring a wealth of experience and expertise to the table. Benjamin King, an American and British Luxembourger, has a diverse background that spans different fields. Despite his initial career as a physicist not panning out, Ben found his calling in the tech world. He co-founded Tumelo, where he served as CTO, guiding the company through its Series A funding round and building a robust engineering team. His experience in leading a start-up through critical growth phases has been invaluable in shaping Quary's development and strategic direction.

Louis Jordan, on the other hand, brings a different but complementary set of skills. With a background in data and fintech, Louis spent four years as a Software Engineer at Amazon, where he honed his skills in handling large-scale data operations. His experience in one of the world's leading tech companies has given him a deep understanding of the complexities and challenges involved in data engineering. Together, Ben and Louis have leveraged their combined expertise to create Quary, a platform designed to address some of the most pressing issues in the data landscape.

What Inspired the Creation of Quary?

The inception of Quary was driven by a critical observation in the data landscape: the significant bottleneck created by the limited number of data engineers. Typically, data engineers constitute a mere 5% of a business’s workforce, yet they bear the responsibility of extracting insights for the remaining 95%. This imbalance leads to overburdened data teams, siloed knowledge, and delayed answers to essential business questions. Ben and Louis recognized that this inefficiency was a major hurdle for many organizations and saw an opportunity to create a solution that could democratize data engineering.

Their vision was to develop a platform that would allow more people within an organization to participate in data transformation tasks, thereby spreading the workload and speeding up the process. By making data engineering more accessible, they aimed to empower analysts and other team members to contribute directly to data projects, reducing the bottleneck created by the over-reliance on specialized data engineers.

How Does Quary Address the Problem?

Quary tackles this challenge by bringing the data engineering process into the browser, making it accessible to a wider audience. The platform allows anyone proficient in SQL to build production-grade data pipelines quickly and efficiently. By connecting directly to data warehouses like Snowflake, BigQuery, and DuckDB, Quary enables users to transform raw data into valuable insights within seconds. This approach not only accelerates the data transformation process but also fosters a collaborative environment where more team members can contribute to data engineering tasks.

Quary's browser-based interface eliminates the need for complex local setups, making it easier for teams to collaborate and manage their data transformation workflows. This accessibility is a key factor in Quary's ability to democratize data engineering. Instead of relying on a small group of specialists, organizations can leverage the skills of a broader range of employees, enhancing overall productivity and efficiency.

What Makes Quary Unique?

Several features set Quary apart from traditional data engineering tools:

1. Browser-Based Interface: By operating entirely within the browser, Quary eliminates the need for complex local setups, making it easier for teams to collaborate and manage their data transformation workflows. This also means that updates and improvements to the platform can be deployed seamlessly, ensuring that users always have access to the latest features and capabilities.
2. Self-Service Analytics: Quary empowers analysts to self-serve, reducing their dependency on data engineers and accelerating the delivery of metrics and insights. This self-service capability is a game-changer for organizations, as it enables faster decision-making and more agile responses to changing business needs.
3. Collaborative Workflows: The platform promotes a collaborative approach to data engineering, enabling more team members to participate in the process and share knowledge. This collaboration not only improves the quality of the data transformations but also helps to build a more cohesive and informed team.
4. Rapid Deployment: With Quary, the time taken to build and deploy data transformations is significantly reduced, allowing businesses to react faster to changing data needs. This rapid deployment capability is particularly valuable in fast-paced industries where timely access to insights can provide a competitive edge.
5. Extensive Documentation and Testing: Quary ensures that all data transformations are well-documented and tested, providing a high level of reliability and transparency. This focus on documentation and testing helps to prevent errors and ensures that data transformations can be easily understood and maintained by other team members.

Who Benefits from Quary?

Quary’s platform is particularly beneficial for fast-growing companies, such as its first customer, a fintech firm. By enabling the growth team’s analysts to self-serve and contribute to data engineering tasks, Quary helps these teams ship metrics faster and provide executives with quicker access to critical business insights. This approach is especially valuable for companies looking to scale their operations without overburdening their data engineering teams.

For example, a fintech company experiencing rapid growth can leverage Quary to streamline its data transformation processes. Instead of waiting for a small team of data engineers to handle all the data tasks, analysts can use Quary to transform data on their own, reducing bottlenecks and accelerating the flow of information. This not only improves operational efficiency but also enhances the company's ability to respond to market changes and customer needs.

How Did Quary Launch and Gain Traction?

Since its launch, Quary has gained attention for its ability to transform the data engineering landscape. The platform’s ease of use, combined with its powerful capabilities, has resonated with businesses looking for more efficient ways to manage their data. The founders, Ben and Louis, have actively promoted Quary, sharing their excitement and vision with potential users and investors. Their combined expertise and passion for solving data-related challenges have been instrumental in Quary’s early success.

Quary's initial traction can be attributed to its clear value proposition and the founders' commitment to addressing real-world data challenges. By focusing on the needs of their target audience and continuously refining the platform based on user feedback, Ben and Louis have been able to build a product that meets the demands of modern businesses. Their hands-on approach to customer engagement and support has also helped to build a loyal user base that is eager to advocate for Quary.

What Challenges Does Quary Address?

Quary addresses several critical challenges faced by businesses in managing their data:

1. Knowledge Silos: By enabling more team members to participate in data engineering tasks, Quary helps break down knowledge silos and promotes a more collaborative work environment. This sharing of knowledge not only improves the overall quality of data transformations but also fosters a culture of continuous learning and improvement.
2. Resource Constraints: With only a small percentage of the workforce typically dedicated to data engineering, Quary’s self-service approach alleviates the pressure on these specialized roles, allowing businesses to do more with their existing resources. This efficiency is particularly important for smaller companies or those with limited budgets, as it enables them to maximize the impact of their data initiatives without needing to hire additional staff.
3. Speed and Agility: Quary’s platform significantly reduces the time required to transform and deploy data, enabling businesses to respond more quickly to emerging trends and insights. This agility is crucial in today's fast-paced business environment, where the ability to make data-driven decisions quickly can provide a significant competitive advantage.
4. Quality and Reliability: By ensuring that all data transformations are well-documented and tested, Quary enhances the quality and reliability of the insights generated. This focus on quality helps to build trust in the data and ensures that decisions made based on these insights are well-founded.

What is the Future Vision for Quary?

The future of Quary looks promising as the founders continue to refine and expand the platform’s capabilities. Their vision is to make data engineering accessible to all, regardless of technical expertise, and to create a more collaborative and efficient data landscape. As Quary grows, it aims to integrate with more data warehouses and expand its feature set, further enhancing its value proposition for businesses of all sizes.

Ben and Louis are committed to continuously improving Quary based on user feedback and evolving industry trends. They plan to introduce new features that will further streamline the data transformation process, such as advanced analytics tools, integration with additional data sources, and enhanced collaboration capabilities. By staying at the forefront of innovation, Quary aims to remain a leader in the analytics engineering space and continue to provide exceptional value to its users.

How Can Businesses Get Started with Quary?

Businesses interested in leveraging Quary’s innovative platform can get started by connecting their data warehouses to the tool. The onboarding process is designed to be straightforward, allowing teams to quickly begin transforming their raw data into actionable insights. With Quary, businesses can unlock the full potential of their data and empower their teams to drive more informed decision-making.

To get started, businesses can sign up for a Quary account and follow the simple setup instructions to connect their data sources. Quary's intuitive interface and comprehensive documentation make it easy for users to get up and running quickly, even if they have limited technical expertise. Once connected, users can start building and deploying data transformations, taking advantage of Quary's powerful features to generate valuable insights.

Conclusion

Quary represents a significant leap forward in analytics engineering, bringing the entire model-test-deploy workflow into the browser

and democratizing access to data transformation tools. Founded by Benjamin King and Louis Jordan, Quary addresses the critical challenges of overburdened data teams and siloed knowledge, enabling businesses to become more agile and collaborative. As Quary continues to evolve, it promises to reshape the way organizations manage and utilize their data, making analytics engineering more accessible and efficient for all.

With its innovative approach, user-friendly interface, and powerful capabilities, Quary is well-positioned to lead the way in transforming the data engineering landscape. By empowering more team members to participate in data transformation tasks, Quary helps businesses unlock the full potential of their data, driving better decision-making and fostering a culture of collaboration and continuous improvement. As the platform continues to grow and evolve, it will undoubtedly play a crucial role in shaping the future of data engineering.