UK

United Kingdom · Learning and development · Entry Level (0-2 years)

Learning Analytics Associate

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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Free to start: a plan built for this role, and a Future Fluency module to try first. No card.

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Where should we send it?

One email: what AI is changing in this job, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

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  • Experience bandEntry Level (0-2 years)
  • Direct reportsNo direct reports
  • Reports toLearning Analytics Analyst
  • UK framework levelUsually someone starting out, or keeping a process running

Also advertised as Junior L&D Analyst · Training Data Assistant · L&D Reporting Support

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

NOCN Level 4 certificate for Data Analysts NOCN · Level 4 · covers 5 of 10 standards
BCS Level 4 Diploma - Digital Modular Programme for Data Analysts BCS, The Chartered Institute for IT · Level 4 · covers 2 of 10 standards
NOCN Level 5 Certificate in Productivity Improvement Practice NOCN · Level 5 · covers 1 of 10 standards
Qualifi Level 7 Diploma in IT Qualifi Ltd · Level 7 · covers 1 of 10 standards
Qualifi Level 3 Diploma in Data Science Qualifi Ltd · Level 3 · covers 3 of 10 standards
Qualifi Level 3 Extended Diploma in IT and Data Science Qualifi Ltd · Level 3 · covers 3 of 10 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Analytics Primer NOCN Level 4 certificate for Data Analysts
Data Analysis BCS Level 4 Diploma - Digital Modular Programme for Data Analysts
Data Analysis in support of Productivity Improvement Projects NOCN Level 5 Certificate in Productivity Improvement Practice
Data Analytics Qualifi Level 7 Diploma in IT
Creating and Interpreting Visualisations in Data Science Qualifi Level 3 Diploma in Data Science

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Trust Fluency keeping the digital world safe
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Your Plan Illustration

Built for Learning Analytics Associate

5 units that map to this job, from the qualifications that cover it.

  1. Data Analytics Primer NOCN · covers 5 of 10 standards Level 4
  2. Data Analysis BCS, The Chartered Institute for IT · covers 2 of 10 standards Level 4
  3. Data Analysis in support of Productivity Improvement Projects NOCN · covers 1 of 10 standards Level 5
  4. Data Analytics Qualifi Ltd · covers 1 of 10 standards Level 7
  5. Creating and Interpreting Visualisations in Data Science Qualifi Ltd · covers 3 of 10 standards Level 3
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Learning Analytics Associate?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • Prompt Engineering (Basic)
  • Data Governance (Practical Application)
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Learning Analytics Associate plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

This job involves pulling and cleaning data from learning platforms and HR systems, so it's accurate before anyone else uses it. You work as the foundation for all learning insights that come after, checking numbers and fixing errors. It suits someone who likes spreadsheets and solving data puzzles.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Microsoft Excel Intermediate

Cleaning raw data, using PivotTables for summaries, applying VLOOKUP/INDEX-MATCH for combining datasets, and writing basic formulas to calculate metrics. This is your bread and butter.

Workday HCM / SAP SuccessFactors (HRIS) Basic

Pulling standard reports on employee demographics, tenure, and basic performance ratings. You'll navigate the user interface with guidance, following existing report templates.

Cornerstone OnDemand / Degreed (LMS/LXP) Basic

Running pre-built reports on course completions, enrollments, and 'seat time'. You'll be manually exporting CSVs for further analysis in Excel, following a clear process.

Tableau Desktop / Power BI Desktop Basic

Connecting to Excel/CSV files, refreshing existing dashboards, and making minor adjustments to charts based on feedback. You'll learn to build simple bar/line charts from established templates.

SQL (PostgreSQL / T-SQL) Basic

Running basic `SELECT`, `FROM`, `WHERE` clauses to query clean, well-documented tables under supervision. You'll be using pre-written queries and making small modifications.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Data Extraction Method Follow established guides; escalate if a new data source is needed or a guide doesn't exist. Choose the most efficient method (e.g., API vs. manual export) for routine tasks; consult on novel data sources. Design and implement new data extraction pipelines; define best practices for data acquisition.
Data Cleaning Rules Apply predefined cleaning rules; escalate any ambiguous data points or new types of errors. Develop and propose new cleaning rules for common issues; implement with manager approval. Establish enterprise-wide data quality standards and governance policies for learning data.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Report Accuracy
The percentage of standard data pulls and reports that are free from errors when compared to the source system.
Target · >98% accuracy

You pull a list of course completions for the Sales team. Your manager checks 10 random entries against the LMS and finds no discrepancies. That's 100% accuracy for that check.

Data Request Turnaround Time
How quickly you can fulfil standard, routine data requests from the L&D team.
Target · Within 48 hours for standard requests

An L&D Programme Manager asks for a list of everyone who completed 'Leadership Fundamentals' last quarter. You deliver it within 36 hours, well within the target.

Data Cleaning Efficiency
The proportion of identified data inconsistencies that you successfully resolve or flag for resolution.
Target · Resolve/flag 95% of identified issues

You find 50 entries where a learner's department is missing. You update 48 of them and flag the remaining 2 for your manager because you can't find the information. That's 96% resolved/flagged.

Adherence to Data Governance
How well you follow our established rules and processes for handling, storing, and sharing sensitive learning data.
  • No data breaches or accidental sharing of sensitive information. All data stored in correct locations. Regular participation in data governance training. Your manager doesn't need to chase you for correct file naming conventions.
Proactive Issue Identification
Your ability to spot potential data problems or inconsistencies before they become bigger issues.
  • You flag unusual trends in report numbers (e.g., a sudden drop in completions that doesn't make sense). You notice a common data entry error pattern and bring it to your manager's attention. You ask 'why does this number look odd?' before being told to.
Team Collaboration & Learning
How effectively you work with your immediate team, ask for help when needed, and absorb new knowledge.
  • You actively participate in team meetings. You ask clear, thoughtful questions when you're stuck, rather than struggling in silence. You apply feedback from your manager to your next piece of work. You offer to help others when your own tasks are complete.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Solving Puzzles

You enjoy the challenge of taking disparate, messy data and making sense of it. Finding that one missing piece of data or fixing a tricky formula gives you a real buzz.

Spending an afternoon tracking down why 10 learners' completion statuses weren't updating in the LMS, eventually finding a tiny configuration error, and fixing it.

Learning and Growing

You're keen to pick up new tools (like SQL or advanced Excel functions) and understand how data helps a business. You actively seek feedback and opportunities to expand your skills.

Volunteering to take an online course on Power Query after seeing your manager use it, then applying what you've learned to automate a manual report.

Making a Real Impact (indirectly)

While you're not directly designing training, you get satisfaction from knowing your accurate data helps the L&D team create better programmes that genuinely help people develop.

Seeing a report you helped prepare being used in a presentation to justify investment in a new leadership programme, knowing your numbers were the foundation.

What frustrates people
  • Dealing with legacy systems that are clunky and slow to extract data from.
  • Spending hours cleaning data only for new inconsistencies to appear next week.
  • Being asked for 'just a quick report' that actually requires hours of data wrangling.
  • Trying to find the 'right' data when it's scattered across multiple, disconnected platforms.
  • The constant battle between what data we want and what data we can actually get.
What this role does not give you
  • Direct programme design or delivery responsibilities.
  • High-level strategic decision-making in L&D (not yet, anyway).
  • A role where you avoid repetitive data cleaning tasks.
  • Immediate, high-visibility impact on every project you touch.

8Who you work with

Your work directly underpins the integrity of all learning data. Accurate data means we can make informed decisions about where to invest our training budget, which programmes to scale, and how to help our employees grow. If the data you provide is flawed, it can lead to misinterpretations of learning effectiveness, potentially misdirecting significant L&D resources and impacting employee development strategies.

Inside the business
  • Learning Analytics Analyst (your direct manager)
  • Senior Learning Analytics Analyst
  • L&D Programme Managers (who run the training)
  • HR Business Partners (who care about employee development)
  • IT Support (when systems play up)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Strong numerical aptitude and comfort working with large datasets.
  • Proven ability to learn new software and technical skills quickly.
  • Experience (even from university projects or internships) with data entry, cleaning, or basic reporting.
  • Excellent organisational skills – you can keep track of multiple tasks and deadlines.
  • A genuine interest in how data can improve learning and development.

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced Excel & Power Query

While SQL and BI tools are great, Excel isn't going anywhere. Mastering Power Query will allow you to automate data cleaning and transformation tasks that currently take hours, freeing you up for more analytical work. It's a huge productivity booster.

M language basics · Automated data refresh · Complex data transformations

  • This week: Watch a few YouTube tutorials on Power Query basics.
  • This month: Try to automate one of your most repetitive Excel data cleaning tasks using Power Query.
  • Month 2: Experiment with connecting Power Query to a web source or a simple database.
  • Month 3: Share your automated solution with your team and explain how it works.

Quick win: Find one CSV file you regularly clean manually and try to build a Power Query script to do it for you.

Intermediate SQL

As you progress, you'll need to pull data directly from databases, not just rely on pre-built reports. A solid grasp of SQL will give you much more flexibility and control over the data you extract, letting you answer more complex questions.

JOIN operations · GROUP BY and aggregate functions · Window functions

  • This week: Complete an online SQL tutorial (e.g., SQL Zoo, Codecademy).
  • This month: Practice writing `JOIN` queries on a dummy database or our internal sandbox environment.
  • Month 2: Try to rewrite one of your complex Excel analyses using SQL instead.
  • Month 3: Ask your manager for a real-world data question that could be answered with an intermediate SQL query.

Quick win: Start by understanding the structure of our key database tables. Just knowing what's where is a massive head start.

11Staying current once you are in

What people here do to keep up
  • Online courses on data cleaning and manipulation in Excel or Python (e.g., DataCamp, Coursera).
  • Participating in internal L&D 'lunch and learn' sessions to understand our programmes better.
  • Attending webinars or reading articles on basic learning analytics concepts and metrics.
  • Shadowing a more senior analyst to see how they approach complex data problems.
  • Joining internal data communities or forums to learn from peers.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering (Basic)

AI tools are becoming ubiquitous. Being able to ask the right questions to get useful answers from large language models (LLMs) will significantly speed up your work, from drafting summaries to generating initial code snippets. Analysts who master this will be far more productive.

  • Clear, concise prompting
  • Context & constraints
  • Iterative prompting
  • Output validation

Data Governance (Practical Application)

As data becomes more central, ensuring its quality, security, and ethical use is paramount. You'll be on the front lines, so understanding the 'why' behind our rules will help you apply them consistently and spot issues early.

  • Data quality rules
  • Data lineage
  • Data privacy principles
  • Metadata management

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Kirkpatrick Level 1 & 2 Understanding
  • Basic Data Storytelling
  • Learning Transfer Awareness

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Data Entry / Administrative Assistant

    1-2 years

    Skills to master

    • Exceptional attention to detail, strong organisational skills, basic Excel proficiency, understanding of data integrity.

    You're ready to move on when

    • You're already spotting errors in data you're entering and suggesting improvements.
    • You've taken initiative to automate small, repetitive tasks using Excel formulas.
    • You've expressed a clear interest in moving into a more analytical role.
  2. 2

    Internship in Analytics / L&D

    6-12 months

    Skills to master

    • Exposure to real-world data challenges, understanding of business context, basic reporting tools, professional communication.

    You're ready to move on when

    • You've successfully completed an analytical project during your internship.
    • You've received positive feedback on your data accuracy and problem-solving.
    • You've built a small portfolio of analytical work, even if it's from university.
  3. 3

    Recent Graduate (Numerate Degree)

    0-1 year (direct entry)

    Skills to master

    • Academic understanding of statistics/data, research methodology, critical thinking, presentation skills.

    You're ready to move on when

    • You achieved good grades in quantitative subjects.
    • You can articulate how your academic projects relate to business data challenges.
    • You're eager to apply theoretical knowledge to practical, messy datasets.

15Where this role leads

The long view: This work can lead to senior analyst roles handling more complex projects, or into managing an analytics team and setting the direction for learning insights.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Learning Analytics Associate is actually changing.

Where it leads

Roles this leads to

The record names a next step, but the catalogue has no page for it yet:

  • Learning Analytics Analyst (Level 2)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Analytics Primer, worked against Learning Analytics Associate.

Data Analytics Primer Level 4

Applied to your work in Learning Analytics Associate

This unit aims to equip learners with a foundational understanding of data analytics, including its applications and the stages of the data analysis lifecycle. Learners will explore various data types and structures, understand the role of data within an organisation, and recognise the importance of GDPR and compliance requirements in data handling.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

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See Your Progress Grow Illustration
Learning Analytics Associate
  • Kirkpatrick Level 1 & 2 Understanding
  • Basic Data Storytelling
  • Learning Transfer Awareness
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Learning Analytics Associate is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Learning Analytics Analyst (Level 2)

    2-3 years in the Associate role

    You'll move from executing tasks under close supervision to owning complete analytical projects from start to finish. You'll be making more independent decisions on methodology and tool usage.

    • Intermediate SQL Writing more complex queries with joins and aggregations.
    • Power Query (M language) Automating data cleaning and transformation pipelines.
    • Survey Design & Analysis Designing effective surveys and analysing open-text feedback.
    • Kirkpatrick Level 3 & 4 Concepts Beginning to explore how to measure behaviour change and business impact.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a lot of the initial grunt work in data analysis can be automated. We're not just talking about using AI; we're talking about making your job easier and letting you focus on the interesting stuff, faster. Imagine less time wrestling with messy spreadsheets and more time actually understanding what the data means.

In Learning Analytics, AI isn't just a buzzword; it's a practical helper. It can take the sting out of repetitive tasks, help you spot patterns you might miss, and even draft your initial communications. We're building an AI-first culture here, and we want you to be part of it from day one. Here's how AI will actually help you in this role:

Thematic Analysis Assistant

Feed thousands of open-ended comments from 'smile sheets' (our Level 1 feedback surveys) into an AI. It'll instantly categorise feedback into themes like 'Instructor Quality', 'Content Relevance', or 'Platform Issues', saving you hours of manual reading. You'll then validate the AI's work, not do it all from scratch.

Automated Report Drafter

Connect AI tools to your basic data outputs (like a simple Excel summary) and get a first draft of a weekly or monthly narrative summary. It'll highlight key trends, outliers, and changes, giving you a solid starting point for your reports, meaning less time staring at a blank page.

Stakeholder Comms Co-Pilot

Got a simple data finding, like 'Course X completion rates dropped by 10% this month'? Ask an AI to draft a clear, jargon-free email to an L&D Programme Manager explaining what this means and suggesting a follow-up. It's great for getting those initial communications out quickly and clearly.

SQL Query Co-Pilot

Use AI assistants (like GitHub Copilot) to translate natural language requests ('Show me all employees who completed the sales training and their quota attainment for the next quarter') into a valid SQL query. This accelerates your data exploration, letting you get the data you need much faster, even with basic SQL knowledge.

Common questions

Common questions

How do you become a Learning Analytics Associate?

Common routes in include Data Entry / Administrative Assistant (1-2 years), Internship in Analytics / L&D (6-12 months) and Recent Graduate (Numerate Degree) (0-1 year (direct entry)). Times vary with prior experience.

Where can a Learning Analytics Associate progress to?

This role can lead on to Learning Analytics Analyst (2-3 years in the Associate role), depending on the skills you build.

What new skills matter most for a Learning Analytics Associate?

Increasingly, Prompt Engineering (Basic) and Data Governance (Practical Application). These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

Three free tools, no account needed. Each one ends with a role, a level and a way in.

Read the Zavmo manifesto to understand how you will be taught Meet your tutors

Or try another one

17Where to go from here

Other roles at Level 2

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in learning and development

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills built here, cleaning data, analysis, visualisation and explaining findings clearly, transfer well. They can lead into HR analytics, people analytics, or data analyst roles in marketing, finance or operations. Data work exists in most industries.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Learning Analytics Associate plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.