- Blog
- 05.16.2025
- Data Productivity Cloud
Empowering Non-Technical Teams with Data: How Matillion Data Productivity Cloud Breaks Down Barriers

Read on to discover how Matillion’s Talent Development Manager transformed HR data analysis with no prior ETL experience.
The ability to extract meaningful insights from raw data is no longer just the domain of technical specialists. Matillion's Data Productivity Cloud is changing the game by making data transformation accessible to everyone – regardless of technical background.
A Non-Technical User's Journey
Meet Hannah Burke, Senior Talent Development Manager at Matillion. With six years at the company, but no hands-on experience with ETL tools, Hannah embodies the type of business user that traditionally would have needed to rely heavily on a centralized data team for insights.
I understand what Matillion does conceptually from working here and have explored the pipeline design canvas as part of interviewing technical candidates, but I've never been into the product really myself – until recently with Data Productivity Cloud.Hannah Burke Senior Talent Development Manager| Matillion
Once a year, Hannah found herself facing a familiar challenge: analyzing data from Matillion's annual review cycle. In previous years, her team had managed the process using Google Sheets and manually created visualizations – a time-consuming approach that limited the depth of insights they could extract.
This time, Hannah was determined to find a better way to handle the approximately 30,000 words contained in the review submissions. As with any People function, maintaining the anonymity of the sensitive data, whilst being able to identify trends, was also a key concern.
From Spreadsheets to Self-Service Analytics
Hannah's initial attempts to analyze the data using tools like Google Sheets hit roadblocks – the dataset consisted of multiple rows of unstructured, free-form text, which such tools aren’t optimized to handle. That's when she turned to Matillion Data Productivity Cloud, curious to see if the platform could help her team derive deeper insights from their performance review data.
For Hannah, this wasn't just about solving a business problem; it was about "drinking our own champagne" and experiencing firsthand the product that Matillion offers to customers.
Getting Started: Breaking Down the Learning Curve
As a non-technical user approaching data transformation tools for the first time, Hannah took some critical first steps to set up for success:
I found it relatively easy to get started. I did one of the training courses/webinars to help me understand some of the language of components, orchestration pipeline, transform pipeline, etc. I followed a video very slowly and carefully step by step.Hannah Burke Senior Talent Development Manager| Matillion
The experience highlights a key strength of the Matillion platform – while it offers powerful functionality, it remains approachable for those willing to try out the low-code interface.
Many HR professionals will resonate with Hannah's main concern – the sensitive nature of the data she was working with. As a SaaS platform, Data Productivity Cloud is secure by design. It uses pushdown architecture to ensure that data never leaves your cloud provider – maintaining true data residency and sovereignty while also meeting enterprise-grade security needs.
The Power of Copilot: AI That Empowers Rather Than Replaces
What truly transformed Hannah's experience was Matillion's Copilot feature. As Hannah encountered unfamiliar territory, Copilot stepped in to bridge the knowledge gap. She also teamed up with fellow Matillioner Susana Cardoso, a Data Engineer who empowered Hannah on her Data Productivity Cloud journey. Susana emphasizes how Copilot transforms the user experience:
Copilot simplifies the transformation process, which is often the biggest part of your workload and can easily become technically challenging. By giving Copilot a brief description of what you’re trying to achieve, it’s able to locate the right source data within your warehouse and generate the necessary pipeline logic to shape it into what you need, essentially turning your business use case into a working pipeline.Susana Cardoso Data Engineer| Matillion
How Hannah Built an AI-Powered Insights Pipeline
Step 1: Hannah began by pulling in the feedback data table she created in a previous orchestration pipeline.
Step 2: She added a Cortex Completion component to perform the initial theme extraction, automatically identifying skills and topics mentioned in each response.
Step 3: Hannah implemented a calculator component to clean and standardize the AI's initial output, ensuring consistent results.
Step 4: Using a simple rename component, she eliminated duplicate columns and provided more descriptive names.
Step 5: Hannah added an Aggregate component that allowed her to combine all the skills into one row using a List Aggregate function. This is needed to prepare the data for the LLM in the next step.
Step 6: She then fed this consolidated list into a second Cortex Completion component, which analyzed the entire dataset of skills to identify the top three most recurring themes.
Step 7: For the final touches, Hannah implemented yet another rename component to make the results presentation-ready.
With the assistance of Copilot, the entire process required no coding knowledge, yet delivered insights that would have previously required dedicated data engineering resources. By empowering team members like Hannah to perform sophisticated data analysis independently, decisions can be made faster without technical bottlenecks.
Business Impact: From Data to Strategic Action
The true test of any data tool is the impact it has on business outcomes. For Hannah's team, the insights generated through Data Productivity Cloud have directly influenced talent management strategies:
We have used the data generated to support the People Business Partners in working with their executives about areas of skill development for their teams. In some cases, it has validated what was felt to already be known in teams, and in other cases, it has generated new information for executives.Hannah Burke Senior Talent Development Manager| Matillion
The result? More targeted development plans that help "motivate, develop, and retain our teams." The team can now collect data from individuals and identify patterns to implement strategic plans to retain key talent.
Transforming the Relationship Between Business and Data Teams
From the data team's perspective, empowering business users like Hannah creates a win-win situation. As Susana explains:
For data teams, the most time-consuming part is often understanding the data and the business context behind requests, while also handling multiple iterations of requests that follow after the initial insights are delivered. When business teams feel empowered to take ownership of building or refining pipelines, it allows data teams to shift their focus back to more complex data problems. And, of course, business teams get quicker, more appropriate answers.Susana Cardoso Data Engineer| Matillion
This new paradigm means data specialists can focus on solving novel problems rather than repeatedly performing similar transformations for different stakeholders – ultimately increasing the overall data productivity of the organization.
Key Takeaways: The Power of Self-Service Data
Hannah's experience demonstrates three important lessons:
- Expand your comfort zone: "Don't be afraid to push yourself out of your comfort zone – there is so much that can be done with data."
- Focus on impact: "Data is all around us and it's easy to get lost in it. We can drive the most business impact by harnessing and refining it with tools like Data Productivity Cloud.
- Learn by doing: "I could have asked the data team to build the pipeline for me, but by doing it myself with their support, I have learned a new skill, and I am now supporting my wider team in understanding what projects they can also use Data Productivity Cloud for."
A New Era of Data Democracy
Matillion Data Productivity Cloud represents a significant step toward true data democratization – where insights can be derived by those who need them most, not just those with specialized technical skills. As Susana summarizes:
With features like Copilot and other AI-powered components within Data Productivity Cloud, it is now easier than ever for business teams to explore and manipulate their own data. Business teams usually have the clearest understanding of their data and the specific questions they need answering.Susana Cardoso Data Engineer| Matillion
By enabling non-technical users like Hannah to directly engage with their data, Matillion is helping organizations unlock the full potential of their data – turning information into action faster and more effectively than ever before.
Matillion's Data Productivity Cloud empowers both technical and non-technical users to transform data into valuable business insights. Learn more about how Data Productivity Cloud can help your organization democratize data access here.
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