Insyt is free to use. Role-based learning, skill paths and resources are organised around the role you have and the career you want.
HOW IT STARTED
The Insyt Story
How a growing challenge in the workplace became a free place to learn.
Where It Starts
Data is everywhere
Data, analytics and AI are transforming how every organisation thinks and works, from the boardroom to the front line.
The Challenge
The skills gap is growing
Specialist skills are now essential for everyone, yet building them is still harder than it should be.
The Aha Moment
Learning in one place
Insyt brings practical learning together for every role.
The Future
A seat at the table
As Insyt grows, more people in every role will feel confident and welcome in conversations about data.
THE PROBLEM
Why Insyt Exists
Data skills are now expected of almost every role, but the training on offer was not designed for the people who need it most.
88%of enterprise leaders call basic data literacy essential for day-to-day work1 DataCamp & YouGov, 2026
60%report a data skills gap in their own organisation1 DataCamp & YouGov, 2026
42%provide foundational data training at scale1 DataCamp & YouGov, 2026
3%of participants complete open online courses, and half never start2 Reich & Ruipérez-Valiente, Science, 2019
Expectation has outrun support
Nearly nine in ten leaders treat data literacy as a basic workplace skill, alongside writing. Fewer than half of organisations train people for it at scale, so the expectation lands on individuals to work it out alone.
Long courses are not finished
Open online courses are abandoned by the overwhelming majority who start them, and most people who sign up never begin. Length is not the only cause, but a course that takes twenty hours competes with a working week that has none spare.
Reading is mistaken for learning
Most material explains and then moves on. Research on how people learn is clear that being asked to recall something, and spacing out when you practise it, does far more than reading it twice.
Where these figures come from
188%, 60% and 42%: DataCamp and YouGov, State of Data & AI Literacy 2026, a survey of more than 500 US and UK enterprise leaders. Industry research, published by a commercial training provider.
23% completion and half never starting: Reich, J. and Ruipérez-Valiente, J. A. (2019), ‘The MOOC Pivot’, Science 363(6423), 130–131. Peer-reviewed, covering 12.67 million registrations on MIT and Harvard courses.
3Recall and spacing beat re-reading: Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J. and Willingham, D. T. (2013), Psychological Science in the Public Interest 14(1), 4–58. Peer-reviewed review of ten study techniques.
WHAT USUALLY GOES WRONG
Five Reasons Training Fails
Every rule Insyt follows answers one of these. They are the difference between content that is read and content that changes what someone does.
Written for the writer
It follows what the author knows, rather than what the learner needs to do on Monday morning.
No practice
People read, nod and forget. Nothing is recalled, applied or checked, so nothing sticks.
No context
Generic examples that match nobody’s job, so none of it transfers to real work.
No ending
No check, no completion and no next step, so learners never find out whether they got it.
No owner
Nobody reviews it, so it quietly goes out of date, and trust goes with it.
How Insyt answers them
Every lesson starts from a real decision, teaches one idea, checks it, asks you to apply it, and carries a review date and an owner.
Material met again after a gap is retained for longer. So lessons end with a recap, courses end with a cheat sheet, and the glossary keeps every definition to hand.
Beginners learn faster from a fully worked example than from being left to work it out. So the example comes before the exercise, with the numbers shown.
Learning styles. There is no good evidence that people learn better when taught in a style they say they prefer. What does help everyone is meeting the same idea in several forms: in words, as a picture, through an example, and as a question to answer.
Sources: 1Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J. and Willingham, D. T. (2013), ‘Improving Students’ Learning With Effective Learning Techniques’, Psychological Science in the Public Interest 14(1), 4–58, which rates practice testing and distributed practice as the two highest-utility techniques of the ten reviewed. 2Pashler, H., McDaniel, M., Rohrer, D. and Bjork, R. (2008), ‘Learning Styles: Concepts and Evidence’, Psychological Science in the Public Interest 9(3), 105–119.
WHY INSYT EXISTS
From Barriers to Better Learning
Insyt removes three common barriers to learning data skills.
The ProblemThe Insyt Approach
Scattered
Useful learning is spread across countless courses, books and websites.
In one place
Role-based learning, skill paths and resources sit together, organised by role.
Behind Paywalls
The most useful material often comes with an expensive price tag.
Free to Use
Insyt is free to use, including role-based learning, skill paths and resources.
Full of Jargon
Many guides assume knowledge that people are still building.
Clear Explanations
Every technical term is defined as it appears, in simple, everyday words.
GUIDING IDEAS
The Principles Behind Insyt
Everything on Insyt starts from one core principle: understanding data should be accessible to everyone. Three principles bring it to life.
Curiosity matters most
The best data work starts with a good question. Anyone with curiosity can learn to find the answer.
Understanding Comes First
Knowing why a method works lets you use it anywhere. Every guide explains the reasoning behind each step.
Better Skills Lead to Better Decisions
When more people understand data, whole organisations make clearer and more confident choices.
FIND YOUR GROUP
Who Insyt Is For
Anyone who works with data, from first job to data leadership. These groups cover the seventeen roles on Insyt, so pick the one closest to your job.
Mia has spent nearly ten years working in data and analytics, and today leads data products and analytics teams. She started her career without a technical background or an engineering degree, drawn in by a curiosity about how decisions are made and what shapes them.
Inspiring mentors helped her find her way. Today she mentors people starting their careers in data, and Insyt is her way of sharing that support with anyone who wants to build their skills.
Being clear about the limits matters as much as the promises.
No certificates or badges
Insyt teaches skills. It does not accredit them, and never implies that it does.
No vendor selling
Tools are covered because people use them at work, never because of a commercial arrangement.
No real client data
Every example is invented. No customer, employee or company data appears anywhere on the site.
No professional advice
Legal, financial and regulatory topics are explained, never advised on. For decisions, ask a qualified professional.
No dark patterns
No streaks, no guilt, no fake urgency. Nothing is timed, and nothing is designed to keep you here longer than you need.
No hidden gaps
Unfinished means it says so on the page, with what is coming next.
ACCURACY
How Content Is Kept Right
Out of date is worse than missing. A reader who is misled once stops trusting everything else.
DefinitionsChecked against the Data & Business Glossary, which is the single sourceEvery release
FormulasRecalculated by hand using the worked example’s own numbersEvery release
RegulationChecked against the regulator’s own text, with the date it was checkedEvery 6 months
Tool behaviourVerified in the current version of the tool, with the version namedEvery 12 months
StatisticsNamed source, year and type. Peer-reviewed research preferred, industry surveys labelled as suchEvery 12 months
Written with AIAI may help draft and suggest. It may not invent a statistic or write regulated content unchecked, and a person reads and owns every pageAlways
Every page carries a review date and a named owner. If you spot something wrong, please say so and it will be fixed.
