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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
Emerging Partner of the Year
Alteryx
Partner of the Year
EMEA
Tableau
Community Impact 2024
EMEA ESMB
DataIQ
Data for Good Champion
Finalist
DataIQ
Best Data Academy or Skills Development
Finalist
Alteryx
Partner of the Year
Europe
DataIQ
Data for Good Champion
Champion
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.
Wed 27 May 2026 | Ellie Kershenbaum
Dashboard Week: EFT Performance
The Brief
For Dashboard Week Day 2 we were tasked with analysing historical ETF (Exchange Traded Fund) performance on the London Stock Exchange using Power BI. We had to transform thousands of individual tables into a high-performance business dashboard that delivers sharp, investor-grade insights
Thu 21 May 2026 | Serena Purslow
DS56 Dashboard Week Day 3: UK Crimes API
For Dashboard Week Day 3, DS56 will be tackling APIs in Alteryx, to build a comprehensive spatial overview of UK crime in Tableau.
Tue 26 May 2026 | Sean Fei
The Consultant's Guide To Consulting: Understanding Your Client's Story
In consulting, one of the most important concepts to grasp, is understand your client's needs and wants fully. It's very easy to miss the mark and misinterpret a client's desires, which is why we construct something called a user role
Wed 27 May 2026 | Amelia Young
Aggregation in Tableau Prep Builder
An overview of what aggregating data is, why we do it and how to aggregate data in Tableau Prep Builder
Wed 27 May 2026 | Kaori Ikarashi
Ranking on Tableau Prep
Ranking in Tableau Prep helps organise data by assigning positions based on values. It is useful for identifying highest, lowest, first, or top-performing records within a dataset. Ranking also helps simplify filtering, grouping, and preparing data for analysis in Tableau
Wed 27 May 2026 | Ben Hayward
Level of Detail Expressions
Level of Detail Expressions in both Tableau Desktop and Prep.
Wed 27 May 2026 | Mila Kholodiy
Cleaning data with clicks in Tableau Prep
Learn how to clean messy data with simple clicks using a real tourism dataset from the Maldives. This beginner-friendly guide covers missing values, data types, unpivoting, and other essential cleaning steps that turn raw spreadsheets into analysis-ready data
Wed 27 May 2026 | Sophie Yeung
Non Equal Joins in Tableau Prep
What is a non-equal join and when would you use it?
Wed 27 May 2026 | Jude Royall
Parameters in Tableau Prep
What are parameters in Tableau Prep? Why would you need parameters? How do parameter use cases vary in Tableau Prep and Tableau Desktop?
Wed 27 May 2026 | Shivam Wadhia
Dashboard Week Day 2: LSE's ETFs
Dashboard week sees DS'ers being given a brief at 9am, making a dashboard based on the brief and then presenting it at 3:30pm.
On day two of dashboard week, DS56 were given data on Exchange Traded Funds traded on the London Stock Exchange
Wed 27 May 2026 | Holly Andersen
Scaffolding in Tableau Prep: Using New Rows to Fill the Gaps
A quick guide to scaffolding your data with Tableau Prep’s New Rows step.
Wed 27 May 2026 | Sharon Orazulike
Dashboard Week: Day 2
Today we were tasked with loading 4000+ London Stock Exchange tables into Power Query, cleaning it and then building a dashboard on Power Bi.
The Brief:
* To have the ability to look at stock exchange at a high level - so looking at volatility, market momentum etc
Want to know more?
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