Data analysis code for analysts: Cleaning, reproducibility and responsible data collection
A ready-made course you customise for your organisation, with a live session deck and two surveys. You only add the 8 details that are specific to your organisation.
- Length
- 45 min
- Lessons
- 6 lessons
- Frequency
- At onboarding of analysts
- Last reviewed
- 21 Oct 2026
A table of orders is grouped by region and summed; a missing region name hides 200 orders
Try it: this is one of 17 interactive activities in the course.
What's included
Three pieces that work together
Copy once, get everything. Learners prepare on their own, you answer questions live, and the surveys tell you what stuck.
Self-paced course
Short lessons with real workplace scenarios, not walls of text.
- 6 lessons, about 45 minutes
- Process, sorting activity, scenario, timeline and quizzes
Live session deck
An AhaSlides presentation to run after the course, in person or online.
- 10 slides
- Quiz, poll, ranking, word cloud slides
- A closing slide for your contacts
Two surveys
Find out what landed, and whether people use it on the job.
- Post-course feedback, about 2 minutes
- 30-day check-in
- Anonymous by default
- Results feed your next refresher
Learning objectives
At the end of this course, learners can
Each objective and the lesson that covers it.
| ID | Objective | Source | Where it's covered |
|---|---|---|---|
| TO 338.0 | Achieve ≥ 80% on the final assessment | - | Whole course |
| SO 338.1 | Load a dataset and find missing, duplicate and inconsistent values before analysing it | Best practice; DAMA-DMBOK data quality [check before build] | Whole course |
| SO 338.2 | Transform and summarise data and predict what a short data-frame call returns | Best practice | Whole course |
| SO 338.3 | Make an analysis reproducible: fixed inputs, documented steps and a re-run that gives the same result | Best practice | Whole course |
| SO 338.4 | Decide whether collecting data from an external source is allowed, and what must be checked first + your info | GDPR (check applicability); EU DSM Directive text-and-data-mining exceptions [check before build] | Whole course |
| SO 338.5 | Report results with the data caveats the reader needs | Best practice | Whole course |
Your part: what a template can't do for you
- Your workplace details: fill in the 8 highlighted fields so the course describes your own policies, contacts and locations.
- Records: record completion in your own LMS or record system.
Course outline
6 lessons, about 45 minutes
Minutes per lesson are an estimate, shared out by page count.
1A dashboard built on dirty data
3 pages
8 min
A dashboard built on dirty data
3 pages
2Loading and cleaning data
3 pages
8 min
Loading and cleaning data
3 pages
3Transforming and summarising
3 pages
8 min
Transforming and summarising
3 pages
4Making analysis reproducible
3 pages
8 min
Making analysis reproducible
3 pages
5Collecting external data responsibly
3 pages
8 min
Collecting external data responsibly
3 pages
6Reporting and final assessment
2 pages
5 min
Reporting and final assessment
2 pages
Live deck and surveys
10 slides to run live, two surveys to close the loop
Pink slides are interactive. Both surveys are anonymous; pink questions are written for this course.
Post-course feedback: 11 questions, about 2 min
- Overall rating 5 stars
- Relevant, realistic, right length, helpful activities agree/disagree grid
- What was most useful? multi-select
- Confidence before this course, and now 1-5 scale
- Confidence in cleaning · transforming · reproducibility · collection rules · reporting caveats grid
- Can someone else re-run your last analysis? multiple choice
- Which data source do you most want checked before use? short text
- I can say ‘I am not sure we may collect this’ without feeling judged. 1-5 scale
- One thing we should change or add open text
- Would you recommend this course? NPS
30-day check-in
- Have you used what you learned since the course? multiple choice
- How confident are you today? Compare with day 1 1-5 scale
- Do you know where to find the analysis standards and the data collection approval route? yes / no / not sure
- A moment where the training helped, or where you weren't sure open text
- Which topics should the next refresher focus on? ranking
Results show whether people use the training on the job, not just whether they finished it.
Make it yours
8 fields to fill in, and you're ready
Everything else is done. These are the details only your organisation knows; each one is highlighted inside the course.
- Link to the engineering standards or style guide
{{ENGINEERING_STANDARDS_LINK}} - Privacy or data protection contact for collection questions
{{PRIVACY_CONTACT}} - Where completion is recorded
{{LMS_OR_RECORD_SYSTEM}} - Link to the post-course and 30-day survey
{{SURVEY_2_URL}} - Who to ask for help or to report a concern
{{HELP_CONTACT}} - Link to the self-paced course
{{COURSE_URL}}
Show all 8 fields
- List of approved tools and versions
{{APPROVED_TOOLS}} - Link to the baseline survey
{{SURVEY_1_URL}}
FAQ
Common questions
Can I run data analysis code for analysts: Cleaning, reproducibility and responsible data collection training online?
Yes. The course is self-paced and online, and the live deck lets you add a live session in the room or online.
How often is this training needed?
At onboarding of analysts, and before a team moves analysis from spreadsheets to code.
Who needs this training?
Analysts, BI developers, marketing and research teams and new data-team hires; run by data leads with L&D.
What records should I keep?
Record completion in your own LMS or record system, so you can show who finished the course and when.
Can I edit the content?
Yes, everything. Change the wording, swap scenarios for ones from your workplace, add your logo, or remove parts that don't apply.
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Ready to run it?
Open the live deck to see how the session runs alongside the course and both surveys.