TECHNOLOGY · 2.5 HOURS
Data Skills for People Who Are Not Analysts
Data Skills for People Who Are Not Analysts teaches managers and specialists who act on figures to check what a number claims, where it came from and whether a comparison is fair. You finish with a checklist already tested on a real table, so decisions rest on numbers that are safe to use.
About this course
Managers and specialists are sent tables, dashboards and summary figures every week and are expected to act on them, often without knowing exactly what was counted, when, or compared with what. A figure such as complaints up 30% can be accurate and still lead to the wrong decision if a filter was left on, a definition changed, or two unlike periods were set side by side. This course teaches people who do not build the numbers to check them quickly before relying on them, with no statistics required.
The course treats every number as a claim and gives you a small set of checks in a fixed order: state the full claim, find its source, definition, date and owner, check the rows behind it, test whether the comparison is fair, and send the data owner one answerable question when a doubt would change your decision. You finish with a five-question checklist in your own words, already applied to a real table from your work and ending in a clear decision on whether the figures are safe to use.
What you will take away
- You will be able to restate a short figure as a full claim that says what was counted, of whom or of what, over what period, and compared with what.
- You will be able to record the source, definition, date and owner behind a figure, and recognise a note that sounds official but leaves those facts unknown.
- You will be able to spot the ordinary ways rows go missing, such as a filter left on, an export that stopped at its limit, or an average that skips blank cells.
- You will be able to apply four tests of a fair comparison and say what would make an unfair one fair, and write a single message to a data owner that can be answered with a fact.
- You will leave with a five-question data checklist applied to one real table, ending in a decision of safe to use, safe to use with a caveat, or ask first.
Who this course is for
- Managers who take decisions on staffing, budgets or suppliers from figures prepared by someone else.
- Coordinators who receive dashboards and weekly reports and pass the numbers on to colleagues or senior leaders.
- Specialists in fields such as HR, operations or service delivery who are asked to comment on trends without being analysts themselves.
- Anyone who can sort and filter a spreadsheet and read a simple chart but wants a dependable way to judge whether a figure can carry a decision.
What you will do
Each lesson teaches one part of the method, works through a realistic example, and ends with a check on a case you have not seen. The course closes with an assessment and then the piece of work you sign.
- 5lessons with a worked example and a check
- 8scenario questions in the course assessment
- Signedthe data checklist, with a record anyone can verify
- 2.5 hoursat your own pace, with progress saved
- 01
Lesson
A number is a claim
This lesson shows that a short figure stands for a longer claim, and sets out its four parts: what was counted, of whom, over what period, and compared with what. You rewrite figures as full claims and mark sentences that leave the claim open.
- A figure on its own says very little
- The four parts of a claim
- What an incomplete claim is not
- Two labels for every sentence
You mark 4 statements from a realistic case and receive an explanation for each one.
- 02
Lesson
Where the number came from
This lesson explains the four facts behind every figure, which are its source, definition, date and owner, and why the definition most often changes a decision. You judge notes about figures and choose the one that gives all four facts.
- Four facts behind every figure
- The definition does most of the damage
- This is not an audit of your colleagues
- Good enough to use, or not yet known
You compare two versions of the same piece of work, choose the stronger one, and see the reasoning behind the answer.
- 03
Lesson
Filters and missing rows
This lesson covers the most common way a correct-looking total turns out to be wrong, which is that some rows behind it are missing. You learn five ordinary causes, including hidden rows in Excel, and mark figures as counting every row or not.
- A total is only as complete as its rows
- Five ordinary ways rows go missing
- Hidden rows and two different totals
- Counts every row, or rows are missing
You mark 4 statements from a realistic case and receive an explanation for each one.
- 04
Lesson
A fair comparison
This lesson gives you four tests of a fair comparison, covering counting, periods, group size and the numbers behind a percentage, and shows how to say what would fix an unfair one. You mark workplace comparisons as fair or unfair.
- Every decision rests on a comparison
- Four tests of a fair comparison
- Unfair is not dishonest
- Fair comparison, unfair comparison, and what would fix it
You mark 4 statements from a realistic case and receive an explanation for each one.
- 05
Lesson
The question before you act
This lesson teaches you to decide whether a doubt would change your decision and, if it would, to write one short message the data owner can answer with a fact. You repair a vague request into a specific question about definition, rows or comparison.
- Would a different number change the decision
- One message, four parts
- What the message is not
- Choosing the one question
You repair a flawed draft so it meets the standard the lesson sets, and your revision is checked against it.
- 06
Course assessment
Using every check together
This course assessment joins the five moves into one method ending in three decisions, and shows how to match the effort to the stakes of each decision. You then apply the whole method to eight situations you have not seen before.
- The method in one place
- Three decisions at the end
- Matching the effort to the stakes
You judge 8 new workplace situations, with feedback on every option, and need 6 correct to pass.
- 07
Final work and signed record
Your checklist
In this final lesson you write the method as five short questions in your own words and apply them to a real table you have been sent. You finish with a decision on the figures and sign the checklist for your record.
- A checklist in your own words
- Applying it to a real table
- Ready to use, or too vague to use
- How your checklist is checked
You write the data checklist for your own work, part by part, and sign it as your record.
GOOD WORK.THE DATA CHECKLIST, SIGNED.
WHAT CHANGES
What the course changes for you and your organisation.
- 01
Decisions rest on sound figures
The checks catch the common and honest errors behind workplace figures, such as an old extract, a changed definition or an unlike comparison, before a plan is built on them. Your organisation makes fewer confident decisions that later turn out to rest on an incomplete number.
- 02
Effort matched to the stakes
You learn to ask whether a different number would change the decision, so time goes on the figures that matter and small, reversible decisions are not delayed. Most figures are cleared quickly once the claim is written out.
- 03
Questions data owners can answer
Instead of asking a colleague to double-check everything, you send one short message naming the decision, its date, the claim and one factual question. Data owners can reply quickly, and decisions go ahead on time.
- 04
Decisions resting on checked numbers
The ONS found that UK firms with weaker management practices were four times more likely to use little or no analysis to support business decisions. Managers who can test where a figure came from and whether a comparison is fair help their organisation act on numbers that are safe to use.
QUESTIONS
Questions about Data Skills for People Who Are Not Analysts
- What is Data Skills for People Who Are Not Analysts about?
- Managers and specialists are sent tables, dashboards and summary figures every week and are expected to act on them, often without knowing exactly what was counted, when, or compared with what. A figure such as complaints up 30% can be accurate and still lead to the wrong decision if a filter was left on, a definition changed, or two unlike periods were set side by side. This course teaches people who do not build the numbers to check them quickly before relying on them, with no statistics required. The course treats every number as a claim and gives you a small set of checks in a fixed order: state the full claim, find its source, definition, date and owner, check the rows behind it, test whether the comparison is fair, and send the data owner one answerable question when a doubt would change your decision. You finish with a five-question checklist in your own words, already applied to a real table from your work and ending in a clear decision on whether the figures are safe to use.
- Who is Data Skills for People Who Are Not Analysts for?
- Managers who take decisions on staffing, budgets or suppliers from figures prepared by someone else. Coordinators who receive dashboards and weekly reports and pass the numbers on to colleagues or senior leaders. Specialists in fields such as HR, operations or service delivery who are asked to comment on trends without being analysts themselves. Anyone who can sort and filter a spreadsheet and read a simple chart but wants a dependable way to judge whether a figure can carry a decision. No specialist background is assumed, and every term is explained before it is used.
- What will I be able to do after Data Skills for People Who Are Not Analysts?
- You will be able to restate a short figure as a full claim that says what was counted, of whom or of what, over what period, and compared with what. You will be able to record the source, definition, date and owner behind a figure, and recognise a note that sounds official but leaves those facts unknown. You will be able to spot the ordinary ways rows go missing, such as a filter left on, an export that stopped at its limit, or an average that skips blank cells. You will be able to apply four tests of a fair comparison and say what would make an unfair one fair, and write a single message to a data owner that can be answered with a fact. You will leave with a five-question data checklist applied to one real table, ending in a decision of safe to use, safe to use with a caveat, or ask first.
- How long does the course take, and how is it taught?
- The course takes about 2.5 hours and is studied online at your own pace. It has 5 lessons, each with a worked example, a practice exercise, and a check on a new case, followed by a course assessment of 8 scenario questions in which you need 6 correct to pass. Your progress is saved to your account.
- Do I get a certificate?
- Yes. When you pass, you sign a record that names you, the course, and the data checklist. Anyone you share it with can verify it online and download it as a PDF. The record confirms what you completed and does not claim compliance with any regulation.
- How much does it cost, and when can I start?
- The course costs £99, paid once by card through Stripe. Access begins as soon as payment is confirmed, and you can save a sign-in to return to the course from any device.
- Can my organisation train a whole team?
- Yes. Individuals can buy any self-paced course online, and organisations can book trainer-led courses for teams, in person or online, through the Experrt Academy.
More technology courses are listed on the self-paced technology courses for non-technical teams page.
THERE IS A NEXT CHAPTER.
Start today, and finish with
the data checklist your organisation can use.
Checkout takes an email address and a card, and access begins as soon as payment is confirmed. When you finish, you sign a record that names you and the data checklist, which anyone you choose can verify online. The record confirms what you completed and does not claim compliance with any regulation.