United Kingdom · Operations · Mid-Level (2-5 years)

Facilities Data Analyst

Here is the whole job, in plain words. What it is, a real day, 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.

Experience bandMid-Level (2-5 years)
Direct reportsNo direct reports
Reports toFacilities Analytics Manager
UK framework levelUsually a coordinator, or early in a professional job

Also advertised as Operations Data Analyst (Facilities) · Building Performance Analyst · Workplace Data Specialist

Built on an analysis of 43,079 real UK job descriptions · grounded in qualifications employers recognise

Start with a free Future Fluency check, tuned to Facilities Data Analyst

Ten quick questions, one per Future Fluency, asked against this role rather than a generic one. About five minutes, and no card.

Start the check, free

1What this role really is

As a Facilities Data Analyst, you'll be the person making sense of all the numbers that keep our buildings running smoothly. Think of it as being a detective for our offices, warehouses, and other sites. You'll dig into everything from how much energy we're using to how quickly a faulty boiler gets fixed. Your work helps us make smart decisions about our physical spaces, ensuring they're efficient, safe, and actually work for the people inside them. It's about translating raw data into clear insights that our Facilities Managers can actually use day-to-day.

2What you'd actually use

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

IWMS / CMMS (Archibus, Planon, ServiceChannel)Intermediate

Running standard reports, performing data entry, validating work order data, and understanding the basic data schema. You'll be in these systems daily, pulling the 'raw material' for your analysis.

BMS / IoT Data (Johnson Controls Metasys, Siemens Desigo)Basic

Viewing and exporting historical trend data from our building systems. You'll understand concepts like BACnet points and how to get basic sensor readings.

Advanced Excel / Power QueryExpert

Mastering Power Query for ETL tasks (Extract, Transform, Load), building complex formulas, and cleaning large datasets efficiently. This is your bread and butter for quick analysis and data prep.

SQL (SQL Server, PostgreSQL)Advanced

Writing complex queries with multiple joins, subqueries, and window functions to pull specific datasets from our CMMS or other databases. You'll create views to simplify reporting for others.

BI & Visualization (Tableau or Power BI)Expert

Designing, building, and deploying complex, interactive dashboards from scratch. You'll be the go-to person for complex DAX (Power BI) or LOD expressions (Tableau) for facilities reporting.

ERP / Financial Planning (SAP S/4HANA or Oracle NetSuite)Basic

Looking up purchase orders and vendor invoices to reconcile facilities spend. You'll understand how to get basic financial data to blend with operational metrics.

3What 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 choice	Coming in	Where you are now	The step above
Report Content & Format	Follows templates, content reviewed by supervisor.	Designs new reports/dashboards for routine requests, content reviewed by manager.	Defines new reporting standards, makes recommendations to leadership without prior review.
Data Cleaning Methodology	Applies established cleaning rules under guidance.	Independently develops and applies cleaning scripts for specific datasets, consults manager on complex cases.	Defines data quality standards and cleaning best practices for the team.
Software/Tool Selection (Minor)	No authority, uses assigned tools.	Can recommend minor tool upgrades or new features within existing platforms (e.g., a new Power BI visual), requires manager approval.	Evaluates and recommends new analytical tools for team adoption (e.g., a new Python library), with budget up to £5K.
Prioritisation of Ad-Hoc Requests	Manager assigns and prioritises all tasks.	Prioritises routine ad-hoc requests within your assigned workload, escalating conflicts to manager.	Manages and prioritises a pipeline of requests for junior analysts, negotiating deadlines with stakeholders.

4How you'll be judged

The scoreboard, honestly: the hard targets, how often each one is actually looked at, and the quiet human signals that never make it onto a dashboard.

Report Accuracy & Timeliness

The precision of your data and the reliability of your delivery on routine reports.

Target · >98% accuracy; 99% on-time delivery

Your monthly utility cost breakdown for the London office is delivered by the 5th working day, with all figures reconciling back to source invoices to the penny. No last-minute corrections needed.

Work Order Data Quality Improvement

How much you improve the completeness and correctness of our CMMS work order data.

Target · Reduce 'missing data' fields by 10% per quarter for assigned sites

After your analysis and feedback, the percentage of work orders missing asset tags in our Manchester warehouse dropped from 25% to 15% in Q2.

Energy Consumption Anomaly Detection

Your ability to spot unusual patterns in energy use that indicate potential issues.

Target · Identify 2-3 significant anomalies per month that lead to investigation/action

You flagged a 15% spike in weekend electricity use at our Bristol office, which led to the discovery of an HVAC unit running unnecessarily, saving us roughly £500 a week.

Space Utilisation Reporting Accuracy

The reliability of your reporting on how our office spaces are actually being used.

Target · Reports within ±5% variance of actual peak occupancy counts (from badge data)

Your Q3 space utilisation report for the HQ showed a peak occupancy of 650 people, and a manual check of badge swipes confirmed 640-665 people, well within target.

Actionable Insights & Recommendations

Your reports don't just present data; they tell Facilities Managers what they should actually do with it.

Facilities Managers regularly refer to your reports when making decisions. They'll tell you your suggestions led to a specific change, like adjusting a cleaning schedule or investigating a specific asset. You're not just providing numbers, you're providing solutions.

Proactive Problem Identification

You're spotting potential issues in the data before they become urgent problems for the facilities team.

You'll bring problems to your manager's attention before they're reported by others. For instance, you might identify a trend of increasing repair costs for a specific asset type, prompting a pre-emptive maintenance review rather than waiting for a breakdown.

Stakeholder Feedback & Trust

How well Facilities Managers and other teams trust your data and analysis.

People come to you directly with data questions or requests, rather than going to your manager first. They'll express confidence in your numbers and rely on your explanations. You're seen as the 'go-to' person for facilities data for your assigned areas.

Documentation & Knowledge Sharing

How well you document your processes and share your knowledge to make the team stronger.

Your analysis methods are clearly documented and easy for others to follow. You'll contribute to our internal knowledge base, making it easier for new team members or colleagues to pick up your work. You're happy to explain how you got to your conclusions.

5Would you like it

The honest version. What people enjoy, and what grinds them down.

What people enjoy

Solving Tangible Problems

You get a real kick out of seeing your analysis lead to a direct, visible improvement, whether it's a building running more smoothly or a clear cost saving.

You identified that a specific HVAC unit was causing excessive energy use, and after your report, it was adjusted, leading to a noticeable drop in the next month's utility bill. That's a win you can point to.

Bringing Order to Chaos

You enjoy taking disparate, messy datasets and transforming them into clear, organised information that people can actually use.

You took a jumble of spreadsheet data from various sites and built a single, clean database that now powers our monthly maintenance reports. It's satisfying to bring clarity.

Continuous Learning & Improvement

You're always looking for better ways to analyse data, new tools to use, or deeper insights to uncover. You enjoy the challenge of figuring things out.

You taught yourself a new SQL function to speed up a query that used to take ages, or you found a new way to visualise space utilisation that made more sense to the Facilities Managers.

What frustrates people

Garbage In, Gospel Out: You'll spend 60% of your time cleaning data entered by field technicians who prioritise closing a ticket over accurate data. Yet, your final report is treated as absolute truth.
The 'Simple Request' Trap: A director asks for 'a quick breakdown of energy cost per department,' not realising it requires merging utility bills, linking meters to floor plans, and allocating space based on outdated occupancy data. This 'quick' task is your entire week.
Fighting for Data Quality: Constantly making the business case for investing in data governance and technician training, only to be told the budget is needed for 'more urgent' physical repairs—which are often caused by the bad data in the first place.
The Black Box Blame Game: When your analysis flags a building as inefficient, you're caught between the on-site Facilities Manager who swears their equipment is fine and the finance team demanding immediate cost cuts.

What this role does not give you

A perfectly clean, ready-to-analyse dataset (ever).
Immediate, dramatic changes based on every single insight you provide.
A quiet, solitary role – you'll be talking to people constantly to understand their data needs and explain your findings.
A role where you only build new things; maintaining and improving existing reports is a big part of it.

6Who you work with

This role directly influences the operational efficiency and cost-effectiveness of our entire property portfolio. Your analysis helps reduce reactive maintenance, optimise energy consumption, and improve space utilisation. Essentially, you're helping us get more value from our buildings and make better decisions about where we invest our money and effort. Get it right, and we save millions; get it wrong, and we're just throwing money at problems.

Inside the business

Facilities Managers (on-site and regional)
Operations Leadership Team
Finance Business Partners (for property costs)
Workplace Experience Team
IT Support (for system integrations)

Outside the business

Utility Providers
IWMS/CMMS Software Vendors (for data queries)
Building Management System (BMS) Integrators

7What you need before you start

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

Proven experience (2-5 years) working with large, complex datasets, ideally within an operational or facilities context.
Demonstrable expertise in SQL for querying relational databases and advanced Excel/Power Query for data manipulation.
Hands-on experience building and maintaining dashboards in either Tableau or Power BI.
A track record of identifying data quality issues and working with stakeholders to resolve them.
The ability to translate business questions into analytical problems and present findings clearly to non-technical audiences.

8What to practise next

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

Basic Python for Data Automation & Analysis

While Excel and SQL are critical, Python offers unparalleled power for automating repetitive data tasks, integrating disparate systems via APIs, and building more advanced analytical models (like basic predictive maintenance). It's becoming the standard for serious data work.

Pandas DataFrames · NumPy for Numerical Operations · API Interactions (Requests Library) · Basic Visualisation (Matplotlib/Seaborn)

This month: Complete an online 'Python for Data Analysis' beginner course (e.g., on DataCamp or Udemy). Focus on Pandas.
Month 2: Recreate one of your existing Excel data cleaning workflows in Python, even if it's clunky at first.
Month 3: Attempt to pull a small dataset from one of our BMS or IWMS systems using its API and Python.
Month 4: Build a simple, automated report in Python that runs weekly and emails you the output.

Quick win: Start by using Python scripts for simple file manipulation (e.g., renaming files, merging CSVs) or automating small, repetitive data cleaning steps you currently do manually in Excel.

9Staying current once you are in

What people here do to keep up

Attending industry webinars or conferences focused on facilities technology or operational analytics.
Joining online communities or forums for Power BI/Tableau/SQL users to learn new techniques and solve problems.
Taking online courses (e.g., on Coursera, edX, DataCamp) to deepen your skills in Python, advanced statistics, or specific facilities data topics.
Participating in internal 'lunch and learn' sessions to share knowledge and learn from colleagues.

10How the AI economy is changing work like this

Before we ask anything of you, here's what we can already say about AI and work of this kind:

The new skill this role is being asked for: Prompt Engineering for Facilities Data

Generative AI and Large Language Models (LLMs) are already transforming how we interact with data. Analysts who can effectively 'talk' to these AIs will be significantly more productive, automating tasks that currently take hours.

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

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 for Facilities Data

Generative AI and Large Language Models (LLMs) are already transforming how we interact with data. Analysts who can effectively 'talk' to these AIs will be significantly more productive, automating tasks that currently take hours.

Context Windows & Token Limits
Temperature Settings
Output Validation & Hallucination Detection
Prompt Chaining

What you’ll use

Skills this role draws on

Technical

Space Utilisation & Occupancy Planning
Total Cost of Ownership (TCO) Analysis
Energy Consumption Benchmarking
Work Order Lifecycle Analysis

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
Junior Data Analyst (any sector)
2-3 years
Skills to master
- SQL querying, advanced Excel, basic BI dashboarding, data cleaning techniques, understanding business requirements.
You're ready to move on when
- Can independently pull and clean data for routine reports.
- Has built and maintained several dashboards in a BI tool.
- Can clearly explain analytical findings to non-technical colleagues.
- Shows a genuine interest in operations or facilities management.
2
Operations Coordinator with Data Focus
3-4 years
Skills to master
- Operational process understanding, data entry accuracy, basic reporting, problem-solving within an operational context.
You're ready to move on when
- Has a deep understanding of day-to-day operational challenges and processes.
- Has taken initiative to improve reporting or data quality in their current role.
- Demonstrates strong analytical aptitude despite a non-traditional data background.
- Is proficient in Excel and has some exposure to databases.
3
Facilities Coordinator / Administrator
3-5 years
Skills to master
- Deep knowledge of CMMS/IWMS systems, facilities processes, vendor management, basic financial reconciliation.
You're ready to move on when
- Has extensive hands-on experience with CMMS/IWMS data entry and reporting.
- Can identify common data quality issues within facilities systems.
- Shows a strong desire to move into a more analytical role and has self-taught some data skills (e.g., SQL basics).
- Understands the 'why' behind facilities data and its impact on operations.

11Where this role leads

The long view:Your journey here is what you make it. We're committed to providing the opportunities and support for you to build a truly impactful and rewarding career, whether you choose a technical specialist path or move into leadership. The data you work with today will literally shape the buildings of tomorrow.

Pay & demand

Pay and demand for this role will appear here, each figure traced to a named authoritative source (e.g. the ONS Annual Survey of Hours and Earnings, under the Open Government Licence). We don’t show numbers we can’t attribute.

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 Facilities Data Analyst is actually changing. In about two minutes, the free confidence check asks where you stand on each of the ten. That's the whole check, and it's what makes the plan yours rather than generic.

12The team that's yours

No two people are taught the same way. This is one-to-one, not one-to-many.

Zavmo is a hyper-personalised AI learning platform. Twelve virtual tutors, each with a different way of teaching, and one orchestration agent that picks the right one for the moment. So every single lesson is shaped around you, your role, and the way you learn. Not a course everyone sits through. A conversation built for you, and no one else.

…and nine more, matched to you after your first chat. Meet all twelve

Start free and meet yours

13What it feels like

A conversation, not a course

Because your tutor knows your role, your projects and your last session, learning sounds like this. And it's different for every single person:

Data AnalyticsLevel 4

Applied to your work in Facilities Data Analyst

The objective of this unit is to equip learners with the knowledge and skills to apply data analytics techniques in decision-making processes. Learners will be able to utilise descriptive, statistical, predictive, and prescriptive analytic methods to transform data into actionable insights, forecast future events, and determine optimal solutions for a given situation.

How the thinking builds

Remember
Understand
Apply
Analyse
Evaluate
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.

One to one, not one to many

No two people run this the same way

A course is written once and handed to everyone. This is assembled around you, and keeps changing as it learns you. Five things it reads, and what each one changes.

Your actual work Every lesson is taught against a live piece of your own work, not a worked example from a textbook.
What you already know The first conversation finds your starting point, so you skip what you can already do and spend the time on what you cannot.
The conditions you learn under Not a learning-styles quiz. The evidence does not support those. The dimensions the research does back, read once and used to shape the plan.
How far you got last time It picks up mid-thought. The tutor knows what you said, what you struggled with, and what it asked you to try.
Which tutor suits the moment Twelve of them, each for a different kind of thinking. The one who walks you through a first idea is not the one who stress-tests it.

See how you learn, free. Eight questions, no sign-up. A directional taster; the diagnostic inside Zavmo goes deeper and keeps adapting.

DemonstrateIllustration

Evidenced on your work in Facilities Data Analyst

You do not finish by watching something. You finish by showing it on the work you already do, against the measures this job is judged on.

Report Accuracy & TimelinessThe precision of your data and the reliability of your delivery on routine reports.Your monthly utility cost breakdown for the London office is delivered by the 5th working day, with all figures reconciling back to source invoices to the penny. No last-minute corrections needed.>98% accuracy; 99% on-time delivery
Work Order Data Quality ImprovementHow much you improve the completeness and correctness of our CMMS work order data.After your analysis and feedback, the percentage of work orders missing asset tags in our Manchester warehouse dropped from 25% to 15% in Q2.Reduce 'missing data' fields by 10% per quarter for assigned sites
Energy Consumption Anomaly DetectionYour ability to spot unusual patterns in energy use that indicate potential issues.You flagged a 15% spike in weekend electricity use at our Bristol office, which led to the discovery of an HVAC unit running unnecessarily, saving us roughly £500 a week.Identify 2-3 significant anomalies per month that lead to investigation/action
Space Utilisation Reporting AccuracyThe reliability of your reporting on how our office spaces are actually being used.Your Q3 space utilisation report for the HQ showed a peak occupancy of 650 people, and a manual check of badge swipes confirmed 640-665 people, well within target.Reports within ±5% variance of actual peak occupancy counts (from badge data)

These are this job's own measures, with its own targets. Nothing is marked evidenced, because nobody has started this yet. Yours would fill in from the work you bring.

Your passport

This isn't a certificate you file away. It's a passport to the life you're designing.

Every credit you earn and every fluency you build adds up: evidence where it counts, carried with you. Zavmo keeps the map: where you are, where you're heading, and the next step, at your pace, around your life. From Facilities Data Analyst to Senior Facilities Data Analyst, and whatever you decide comes after.

Level 3 · in progressAI Fluency→ Senior Facilities Data Analyst→ your design

Where this takes you

Your journey here is what you make it. We're committed to providing the opportunities and support for you to build a truly impactful and rewarding career, whether you choose a technical specialist path or move into leadership. The data you work with today will literally shape the buildings of tomorrow.

See Your Progress GrowIllustration

Facilities Data Analyst

Space Utilisation & Occupancy Planning
Total Cost of Ownership (TCO) Analysis
Energy Consumption Benchmarking
Work Order Lifecycle Analysis

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.

14The 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

Facilities Data Analyst is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

Senior Facilities Data Analyst
3-5 years in role
Level 3 (Senior)
- Predictive Maintenance (PdM) Modelling: Building basic models to forecast asset failure.
- Capital Expenditure (CapEx) Forecasting: Developing defensible long-range capital plans.
- Advanced SQL/Python: Writing more complex scripts for data integration and automation.
- Data Governance Leadership: Taking ownership of data quality initiatives and standards.

Working with AI on the job

Working with AI

Where AI is starting to help

Imagine spending less time on tedious data cleaning and more time on high-impact analysis. AI isn't just a buzzword here; it's a practical tool that can seriously boost your productivity as a Facilities Data Analyst. We're actively exploring and integrating AI to make your day-to-day work smoother and more insightful.

Truth is, a lot of facilities data work is repetitive. AI can take a huge chunk of that off your plate, freeing you up for the more interesting, strategic stuff. We're building an internal AI Productivity Hub to help you get started, offering tools and guidance to automate the mundane and accelerate your insights. Here's a glimpse of how you'll be using AI to get ahead:

Automated Work Order Triage

Use Natural Language Processing (NLP) to read the text descriptions of incoming maintenance requests. AI can automatically classify the problem type (HVAC, plumbing, electrical), assign priority, and route it to the correct trade group, bypassing manual dispatch. This means less time sifting through tickets and faster resolution for our buildings.

Anomaly Detection for Energy Hogs

Deploy machine learning models to analyse thousands of real-time Building Management System (BMS) data points. The AI automatically flags assets (like an air handler) that are consuming anomalous amounts of energy, indicating a potential fault days before it triggers a standard alarm. You'll spend less time manually reviewing data and more time investigating true issues.

Smart Regulation & Lease Summariser

Feed new municipal building codes, sustainability mandates, or complex lease documents into a Large Language Model (LLM). The AI generates a concise summary of key obligations, dates, and potential financial impacts on your portfolio. No more slogging through hundreds of pages just to find the critical bits.

Executive Narrative Generation

After creating your monthly performance dashboards, use a generative AI tool to draft the executive summary. It can translate key data points and trends (e.g., 'Energy use in the NE region is up 7% MoM') into a coherent business narrative ('...driven by colder weather and the recent server room expansion'). This saves you time on report writing and lets you focus on the 'what next'.

Common questions

How do you become a Facilities Data Analyst?

Common routes in include Junior Data Analyst (any sector) (2-3 years), Operations Coordinator with Data Focus (3-4 years) and Facilities Coordinator / Administrator (3-5 years). Times vary with prior experience.

Where can a Facilities Data Analyst progress to?

This role can lead on to Senior Facilities Data Analyst (3-5 years in role), depending on the skills you build.

What level is a Facilities Data Analyst in the UK?

This role aligns to RQF Level 3 on the UK framework, a guide to the depth of qualification it maps to, not a hard entry bar.

What new skills matter most for a Facilities Data Analyst?

Increasingly, Prompt Engineering for Facilities Data. These are the areas where the higher-paid, future-proof work is heading.

The honest bit

You’ve started things before

Most of them were built for a room full of people who aren’t you. A cohort moves on whether or not your week allowed it, and by the third week the thing you’re behind on becomes the reason you stop opening it.

There’s no cohort here, and no timetable to fall behind. Before anything starts, Zavmo asks when you’re sharpest and how long you can realistically sit down for, then builds the sessions around those answers. A bad fortnight changes your pace. It doesn’t put you behind.

And you only pay once you start learning. Searching and planning are free, and you can cancel any time — so the cost of finding out is an afternoon, not a year.

What it costs

Less than one coaching session. Every month.

A single career-coaching hour costs more than a month of this, and it ends when the hour does. Zavmo doesn't. It's £70 a month, about £2.30 a day, for a companion that knows a Facilities Data Analyst, works on the job you actually do, and keeps going at your pace rather than a timetable's.

Searching and planning stay free. You only pay when you start learning.
Your credits are yours. Regulated, and they don't vanish when a subscription ends.
Cancel any time and billing stops. No notice period, no minimum term.

Your path, personalised

You have the map. Walking it is the part we do together.

This route runs to 9 national skill standards. That is a real journey.

Zavmo shapes a learning experience as unique as you are. It fits how you learn, your pace and the work you already do. Every step stays benchmarked to recognised national standards. That’s the plan for becoming a Facilities Data Analyst: personal to you, and it still counts. The first steps are free.

Independent research finds well-designed intelligent tutoring performs nearly as well as one-to-one human tutoring: VanLehn (2011), Educational Psychologist.

A private tutor in the UK averages £35–40 an hour . Zavmo is £70/month.

A Zavmo curriculum screen: a three-month plan built for a customer support lead, five Ofqual-regulated units and a hundred and ninety-six credits. — A real plan on learn.zavmo.ai: Ofqual-regulated units, credits, and a three-month run at your own pace.

Start free No commitment. See your first steps free.

15Where to go from here

Other roles at Level 3

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

Other roles in Operations

Stay in the field you know and move sideways rather than up.

If you leave this industry

The analytical skills you'll gain here are highly transferable. You could move into other data analysis roles within Operations (e.g., Supply Chain Data Analyst), Finance (e.g., Financial Planning Analyst), or even into specialist roles in property technology (PropTech) companies. The ability to translate data into business value is always in demand.

Not sure this is the right direction?

Work out what you actually want from work first, then come back and see which roles fit it. Takes about ten minutes.

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. Build my plan, free Here's the first ten minutes: a 2-minute confidence check → your personalised roadmap → meet the tutors matched to you. No card, cancel any time. 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.

Facilities Data Analyst

What's rising in its place

Prompt Engineering for Facilities Data

Skills this role draws on

Technical

How you actually get there, here

Junior Data Analyst (any sector)

Operations Coordinator with Data Focus

Facilities Coordinator / Administrator

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

Roles this leads to

No two people are taught the same way. This is one-to-one, not one-to-many.

A conversation, not a course

No two people run this the same way

This isn't a certificate you file away. It's a passport to the life you're designing.

Everything else the record holds

The career path, and where it branches

Senior Facilities Data Analyst

Where AI is starting to help

Automated Work Order Triage

Anomaly Detection for Energy Hogs

Smart Regulation & Lease Summariser

Executive Narrative Generation

Common questions

You’ve started things before

Less than one coaching session. Every month.

You have the map. Walking it is the part we do together.