Ep11: Hugo Lu, Orchestra
Ep11: Hugo Lu, Orchestra
Learn how Orchestra is helping lean data teams focus on creating business value with it's no-code data orchestration and observability capabilities.
Welcome to the OxIgnite Podcast hosted by Yusuf Raza and Michael Hutson - two entrepreneurial MBA students at the University of Oxford. Together, we navigate the dynamic journeys of Oxford-linked founders, venture capitalists, and trailblazing innovators. Our mission? To fuel the fire in Oxford's next generation of boundary-pushing change-makers.
In today's episode, we speak with Hugo Lu, the Founder and CEO of Orchestra.
Orchestra is a no-code/low-code data orchestration and release pipelining tool designed for lean data teams.
It streamlines data orchestration tasks, eliminating the need to delve deep into complex open-source orchestration frameworks.
In this episode, we learn about data orchestration from the point of view of a data engineer, and the need for a tool like Orchestra to enable lean data teams to spend more time on creating business impact.
We learn about Hugo's professional trajectory, from finance to data engineering, and how his first-hand experiences as a data engineer influenced the inception of Orchestra.
As always, we also cover advice for fellow budding entrepreneurs and tips on maintaining holistic well-being as a founder!
Get ready, get set, get Oxignited!
List of Topics Covered:
Orchestra’s Introduction and Value Proposition: Orchestra is a no-code/low-code data orchestration and release pipelining tool designed for lean data teams. It streamlines data orchestration tasks, eliminating the need to delve deep into complex open-source orchestration frameworks.
Understanding Orchestra: Hugo provided an analogy explaining digital orchestration by detailing the processes a data team undergoes to create a dashboard that depicts a product's usage.
Why Orchestration Matters: Hugo described a shift in data teams' priorities from infrastructure building to delivering business value. He drew parallels with past custom-built data connectors, emphasizing how Orchestra offers a standardized solution.
Current State of Orchestration: Compared to tools like Airflow, which demand extensive Python coding, Orchestra promises a quicker and more streamlined process for orchestration.
Orchestra's Target Audience: Orchestra focuses on serving data teams within organizations, particularly those of 1 to 6 members who spend excessive time on pipeline development instead of deriving business value.
Hugo's Career and Inspiration: Hugo's career started in finance, transitioned to data engineering, and he observed firsthand the challenges of data orchestration with limited resources, motivating him to found Orchestra.
Entrepreneurial Insights from Hugo:
Hugo began Orchestra due to his profound passion for solving orchestration problems.
He underscored the significance of time discipline, learned from his analyst role, for startups.
Emphasized the value of maintaining good relationships and authenticity to navigate entrepreneurial challenges.
Current Status and Future of Orchestra:
The Orchestra team is working on the first version of their product, with a planned launch in September.
Announcements of successful fundraising and new team members.
Goals for product development, team expansion, and user onboarding.
Challenges and Solutions:
Hugo discussed the initial challenges of fundraising and hiring, alongside anticipating future challenges in finding the right product-market fit.
Hugo believes in the value of in-person collaboration and is planning to work from a space in King's Cross.
Advice and Perspectives: Hugo advised aspiring founders to have a deep connection with the problems they aim to solve and not just see startups as a status symbol. He also shared personal insights on well-being, emphasizing a balanced diet, openness to opportunities, and maintaining social connections.
Summary
Today’s guest on OxIgnite is Hugo Lu, the Founder & CEO of Orchestra.
Orchestra is a no-code data orchestration and observability tool for lean data teams. Instead of learning and deploying an open-source orchestration package, Orchestra helps data engineers trigger and co-ordinate jobs across the whole stack using a no-code interface and handles orchestration and alerting.
Understanding Orchestra in Simple Terms: Hugo emphasizes the importance of understanding a data team's operations. As an analogy, he explains how a CEO might request a dashboard depicting the previous month's product usage by each customer. Data teams need to:
Retrieve the scattered data.
Centralize it into a data lake or warehouse.
Transform and cleanse the data for relevance.
Ensure the data's quality through testing.
Finally, create the dashboard.
Connecting and aligning these different tools and processes is known as digital orchestration, the main issue Orchestra aims to address.
Why Orchestration Matters: Hugo points out a paradigm shift in data teams' priorities: from infrastructure building to delivering business value. Orchestra helps facilitate this by reducing the time spent on building and maintaining pipelines, allowing data teams to focus more on generating business value.
He draws an analogy with the past need for custom-built data ingestion connectors, such as those for Salesforce. Today, it's inefficient for every company to construct their connectors or orchestration pipelines since many are dealing with similar challenges using identical tools.
Orchestra offers a standardized solution to this repeated effort, ensuring teams spend more time focusing on business value.Current State of Orchestration: Historically, orchestration has been dominated by tools like Airflow, established around 2014. While incredibly versatile, Airflow demands users define everything in Python code, making it a robust but often overly complex solution. Other open-source tools have emerged with a narrower focus on data teams.
Still, the main drawback remains: significant time is needed to establish and maintain these systems. For instance, deploying a simple task like "print hello world" might be straightforward, but managing hundreds of tasks becomes a daunting endeavor.Orchestra’s Value Proposition: For teams unfamiliar with the intricacies of tools like Airflow, the learning curve can be steep. Orchestra, on the other hand, promises a quicker start to orchestration and a more streamlined maintenance process.
The key advantage for data teams is being able to execute orchestration tasks efficiently without delving deep into the complex mechanics of open-source orchestration frameworks.Orchestra’s Focus on Serving Data Teams: Hugo emphasizes Orchestra’s focus on serving data teams within organizations and shares the specific subset of data teams that they are targetting. The ideal customer profile for Orchestra isn't dictated by the size of the data team but by the nature of their work.
Orchestra is targeting data teams, typically of 1 to 6 people, that spend an excessive amount of time building and maintaining data pipelines when they should be deriving business value.
Hugo mentions that while Orchestra’s current focus is on a specific type of data persona, he eventually wishes to create a flexible product that can cater to a broader audience.Hugo's Career Journey: Hugo's professional journey began in the finance sector, post which he ventured into strategy and operations and subsequently transitioned into data engineering. His educational background includes a degree in PPE and a Masters in Development Economics from Oxford.
He initially joined banking at Rothschild in London, after which he moved to the strategy team of JUUL, a rapidly scaling e-cigarette company. During his tenure at JUUL, Hugo recognized the significant lack of data, which pushed him to learn data engineering.
This transition was further solidified during his time at Codat, a London-based fintech, where he witnessed firsthand the challenges of data orchestration, especially with limited resources.Inspiration Behind Starting Orchestra: Hugo's motivation to start his own company came from personal experiences and frustrations he faced in the data engineering space. He recounts a moment when he was reviewing a complex repository, which was overly intricate for simply triggering jobs.
Hugo's vision for his venture stems from a desire to create a streamlined process for data engineers, enabling them to bypass redundant infrastructure management tasks. He aspires to develop a solution that allows data engineers to focus on generating business value without getting bogged down by the infrastructure's intricacies.
Hugo’s firsthand experiences as a data engineering place him very well to solve the challenges data engineers face daily and introduce a more efficient solution in the data orchestration space. He envisions a future where data engineers can work efficiently without incurring unnecessary costs or deploying cumbersome processes.Background and Education: Hugo attended Oxford where he primarily focused on the technical aspects of his degree. He shares that his background in PPE (Philosophy, Politics, and Economics) surprisingly gave him a foundational understanding of building software products due to its blend of technicality and understanding of market implications.
Entrepreneurial Learnings from Orchestra:
Hugo started Orchestra as a solo founder because he was deeply passionate about building an orchestration solution.
He learned the importance of time discipline from his past role as an analyst in an investment bank, and this is very important at an early stage startup too.
Mistakes are a part of the journey. Maintaining good relationships and being authentic makes it easier for people to forgive those mistakes.
Current Status and Future of Orchestra:
The team is working on V1 of their product, aiming to launch in September.
Hugo excitedly announces new team members and successful fundraising for a small pre-seed round.
The next steps include product development, team expansion, and getting users onboarded.
Challenges and Solutions:
Initial challenges included fundraising, especially in the changing tech climate and hiring talented software engineers.
Future challenges revolve around finding product-market fit and building the right solutions for the right audience.
Building Teams Across Geographies: Hugo believes in the benefits of in-person collaboration, especially in the early stages of a startup. He is looking forward to working from a space in King's Cross, provided by a venture capital firm.
Advice for Aspiring Founders: Hugo believes that potential founders should deeply resonate with the problems they want to solve. Starting a company should not just be a matter of prestige but a genuine passion for solving a real issue. Taking that leap of faith, however daunting, is necessary to get started.
Well-being and Stress Management: For maintaining balance, Hugo emphasizes the importance of a healthy diet, being open to opportunities, and staying socially active.
Links:
Hugo Lu’s Data / Data Engineering Blog
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