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Enhancing your data team with ours
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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Best Data Academy or Skills Development
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Partner of the Year
Europe
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Data for Good Champion
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Data for Good 2021
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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 27 Jan 2026 | Adrienne Zhang
Tips for Using Containers in Tableau: Part 2
This is part 2 in a two part series. See part 1 for a description of what containers are and how to use them.
Today, I want to answer some more FAQs about containers!
What are the “tiled” items appearing in my item hierarchy?
These are Tableau’s way of trying to help structure your dashboard
Tue 27 Jan 2026 | Adil Ahmad
Dashboard Week Day 2- Accessibility
The task we were given today for dashboard week was to design a dashboard for people that may have different accessibility requirements
Tue 27 Jan 2026 | Francesca Plaskett
Accessibility - Dashboard Week (Day 2)
Find out about my second day of dashboard week focussing on accessibility.
Mon 26 Jan 2026 | Tomo Mensendiek
Scaffolding in 3 Min
Scaffolding is the art of adding rows to your dataset. Why would you want to do this?
Imagine you had a new years resolution to work out every day for January
Tue 27 Jan 2026 | Kib Cheung
Dashboard Week Day 2: Accessibility
Building an inclusive dashboard in Power BI was a hurdle, especially switching from Tableau. I focused on semantic ordering and alt text, testing with a screen reader to ensure it didn't just say "object." It turns out good design is just as much about how it sounds as how it looks
Tue 27 Jan 2026 | Aisha Senkubuge
Dashboard Week Day 2: Accessibility
The Brief
Day 2 began with a discussion about accessibility and inclusivity in data visualisation. We talked about how we never know who will be viewing our work and the various impairments, conditions, and disabilities that can impact how people interact with visualisations
Tue 27 Jan 2026 | Tyler Green
Dashboard Week: Day 2 - Designing for Accessibility
For Day 2 of Dashboard Week, the challenge shifted from pure analysis to inclusive, accessible design
Mon 26 Jan 2026 | Sita Pawar
Tableau Table Calculations 101
Tableau's Table calculations are an absolute must for anyone developing their Tableau skills
Tue 20 Jan 2026 | Nicola Huetz
Plan, plan, plan, plan...your data preparation
What to do before even opening the data prep tool of your choice.
Sat 24 Jan 2026 | Nicola Huetz
To tile or not to tile - How using containers will make your life easier
What are containers in Tableau Desktop and how can we use them to make our lives easier?
Thu 15 Jan 2026 | Vivien Lee
Sketching a Story - Planning Data
In week two, whilst we were having fun learning how to use Tableau and Tableau Prep, we also learnt lots about the importance of planning. What's going to be the best approach when it comes to our first client project? We should probably start with a plan
Mon 26 Jan 2026 | Jacob Aronson
How Spread Out is my Data? Pros and Cons of Different Dispersion Metrics
Analysts typically summarize the distribution of a dataset using three kinds of metrics: center, shape, and spread. The center of a dataset is typically quantified by measures of central tendency, such as mean and median
Want to know more?
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