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Our consultants come armed with both technical and soft skills to support you to make the most of your data.
The Data School has been paramount to our success at JLL. It has allowed us to bring in highly skilled Tableau and Alteryx consultants. It saves considerable time trying to recruit contractors as I know their skills and training are to the highest standard. Over the past 5 years my team has developed analytical insights which have generated multi million dollar savings of which a considerable amount can be attributed to the Data School consultants we have had working on projects.
Paul Chapman, Global Director of Performance Management, BI and Innovation at JLL
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Community Impact 2024
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What our consultants are working on
We believe that sharing knowledge and expertise is key to driving innovation and growth in the data community. That's why we're excited to share our latest insights, tutorials, and industry trends with you through this blog.
Written by our team of experienced data consultants, these posts aim to solidify their own learning while giving back to the community.
Tue 16 Jun 2026 | Sean Fei
How To Add Custom Shapes In Tableau Desktop
Recently, I was working on a Makeover Monday where there were many different GPUs for a few different brands. Seeing that there were not a massive amount of GPUs, I made the decision to individually grab the images, and insert them into my Tableau workbook
Tue 16 Jun 2026 | Jacob Aronson
Have Hydration Breaks "Broken" the 2026 World Cup?
The 2026 FIFA world cup has arrived, introducing multiple changes to the tournament’s format like a 3 country hosting tandem and an expanded 48 team field
Tue 16 Jun 2026 | Carla Villafana
Did I Exceed My Target?: How To Create a Conditional Formatting Parameter on Power BI
Let’s say your client wants you to build a chart that shows which products have exceeded the company’s sales target. However, since the sales target is subject to change over time, they would also want the flexibility to adjust the target if needed
Tue 16 Jun 2026 | Jorge Sempere
Why I am Glad I Had to do my Final Interview Twice
When I didn’t get into The Data School after my first final interview, I got a message that I will never forget:
“We know you have potential, but we want to see more from you”
At the time, it hurt, but looking back now, it was probably the best thing that could have happened to me
Fri 12 Jun 2026 | Mel Niere
What did it take to get into DSNY12?
Meet the newest members of Cohort 12 at The Data School New York.
This cohort brings together a strong group of emerging data talent, with thoughtful approaches to analysis, visualization, and storytelling
Fri 12 Jun 2026 | Daniel Bostrom
Tables vs. Views
From the perspective of a data analyst, tables and views can seem interchangeable
Fri 12 Jun 2026 | George Rycroft
Translytical Task Flows in Fabric & Power BI - A Proof of Concept
In May 2025, Microsoft Fabric introduced an innovative new feature to their software. Translytical Task Flows (TTFs). These tools allow static reports in Power BI to become tools which enable action. I recently explored the capabilities of these new functions on a project with a client
Fri 12 Jun 2026 | Kate Loder
Creating fields parameters in Power BI
Creating parameters in Power BI is a lot more straightforward than you might think. Power BI has predefined capabilities for creating these with ease, which makes them nice and simple to create and add in to reports to enhance interactivity
Fri 12 Jun 2026 | Vaishnavi Shankar
Mastering the Bump Chart in Power BI Using RANKX.
When visualising data over time, a standard line chart is usually the go-to. But what if your goal isn't just to show growth, but to show competition?
If you want to see how different business units rank against each other over time, a Bump Chart is the perfect tool
Fri 12 Jun 2026 | Martin Regan
How I Used Snowflake Cortex Code to Build an Automated LEGO Data Pipeline (and Write this Blog Post)
Introduction
I wanted to find the rarest LEGO minifigs in existence — the ones that appeared in a single set, in a quantity of one, decades ago. To get there, I needed a proper data pipeline: paginated API ingestion, raw JSON landing in Snowflake, modelled views, and idempotent reloads
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