Description

A focused course, tailored for you

From Ops Tickets to a Revenue Analytics Portfolio

Name: From Ops Tickets to a Revenue Analytics Portfolio
Price: 199 USD
Availability: InStock

A skills course for an operations specialist moving into business analytics, built around the four artefacts a hiring manager actually opens.

Your LinkedIn headline says transitioning into business analytics. The recruiter scrolling past it on Tuesday morning has seen that exact phrase ten times already today, and not one of those profiles linked to anything they could actually open.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

The honest gap in an operations-to-analytics move is not technical. SQL is learnable in a weekend, pandas in a week, a dashboard tool in an afternoon. The gap is portfolio evidence that the operations work was already analytics work in disguise. Tickets resolved, revenue support escalations triaged, process improvement loops closed: every one of those is a dataset with a clean before-and-after and a stakeholder who cared about the answer. The career-page job descriptions ask for cohort analysis, churn signals, CSAT-to-revenue links, cycle-time reduction. You have lived all four. What is missing is the artefact that proves it, packaged so a hiring manager can open it in thirty seconds and forward it to the team. This course closes that gap by building the four artefacts a hiring manager actually opens, then wrapping them in a resume and a portfolio page that translates ops vocabulary into BA vocabulary.

What you walk away with

A public portfolio page with four artefacts a BA hiring manager can open and forward in under thirty seconds.
A churn cohort and a CSAT-to-revenue regression built from realistic customer-service data, with the assumptions written out in plain English.
A process-improvement before-and-after that translates your operations work into the cycle-time and cost language analytics teams use.
A resume that reads as a business analyst resume, not an operations resume with analytics keywords sprinkled on top.
A clear weekly interview-prep cadence covering SQL pair-coding, case studies, and the behavioural questions that trip up career-changers.

The 12 modules

Module 1. The portfolio audit a hiring manager runs in 30 seconds

Open the actual job descriptions you are applying to and reverse-engineer the four artefacts a hiring manager scans for. Map each artefact to a dataset you can build from public data plus your own anonymised operations experience. Write the one-line portfolio promise that decides whether the hiring manager clicks through or moves on to the next candidate. Output is the portfolio brief that anchors every module after it.

Module 2. SQL from a customer-service table, not a tutorial dataset

Build SQL skills against a realistic customer-service support-ticket schema with tickets, customers, agents, products, and resolution states. Cover joins, window functions, date arithmetic, and the seven query patterns that come up in BA interview pair-coding rounds. Every query you write maps to a question a revenue support team actually asks, so the practice doubles as portfolio raw material for later modules.

Module 3. Python pandas for cohort and revenue analysis

Move the same dataset into pandas and build the analytical muscle that SQL alone cannot reach. Cohort tables, pivot tables, groupby aggregations, time-series resampling, and the missing-data handling that separates a clean analysis from a misleading one. Output is a reusable notebook template you can clone for every future analysis, written so a hiring manager can read it without running it.

Module 4. The churn cohort artefact for your portfolio

Build the first hero portfolio piece end to end. Pick a churn definition that survives a hiring-manager challenge. Build the cohort table, calculate retention by cohort week, surface the two factors that explain most of the variance, and write the plain-English narrative around it. Publish the notebook to a public GitHub repo and the chart to the portfolio page. This single artefact has more signal than any certification you could list.

Module 5. CSAT-to-revenue regression with assumptions written out

The second hero artefact, built from customer service satisfaction data joined to revenue or renewal data. Cover simple linear regression, the difference between correlation and causation in stakeholder language, the four assumptions that need stating, and the chart that communicates the result to a non-analyst executive. The discipline of writing the assumptions out is what separates a junior BA hire from an unhired bootcamp graduate.

Module 6. Process improvement before-and-after in analytics vocabulary

Translate your operations process-improvement work into a cycle-time analysis a BA team would publish. Build the before-and-after measurement, the root-cause Pareto, and the cost-of-delay number. Frame the work using the language an operations or analytics director actually uses, not the operations-team vocabulary the recipient is currently using. This module turns your existing experience into portfolio gold without faking new projects.

Module 7. One dashboard a non-analyst can read in 30 seconds

Build the fourth hero artefact, a single executive dashboard in Tableau Public or Power BI. Cover the three-question test, the colour-and-typography rules that stop a dashboard looking amateur, the filter-and-drilldown logic that separates a static report from an interactive tool, and the publish-and-share step that makes the dashboard linkable from your LinkedIn. The dashboard is the artefact recruiters share around the office.

Module 8. The portfolio page that ties it together

Build the public portfolio page (GitHub Pages, Notion, or a simple personal site) that hosts the four artefacts. Cover the structure a hiring manager scans, the one-paragraph case study per artefact, the about-section narrative that bridges ops and analytics, and the call to action that makes contacting you obvious. The portfolio page is what your LinkedIn headline links to, and what makes the rest of the course pay off.

Module 9. The resume rewrite from ops vocabulary to BA vocabulary

Rewrite your resume around the four portfolio artefacts and the seven measurable wins from your customer service, revenue support, and process improvement work. Cover the bullet-point grammar that applicant-tracking systems parse cleanly, the keywords that map your operations experience to the BA job descriptions, and the one-page rule. The output is the actual resume file you will send to the next twenty applications.

Module 10. The LinkedIn rewrite a recruiter actually responds to

Rewrite the LinkedIn profile around the new positioning. Cover the headline formula that beats transitioning into business analytics, the about-section narrative that demonstrates analytics thinking instead of claiming it, the featured-section setup that surfaces the four portfolio artefacts on the profile itself, and the connection-request template that gets junior BAs to accept and have a coffee chat.

Module 11. Interview prep the week before a BA round

The week-before checklist for a junior BA interview. SQL pair-coding warmup using the patterns from module two. The three case-study frames hiring managers ask, with worked examples. The behavioural questions that catch career changers (why analytics, why now, what is your weakness) with answer structures that turn the operations background into the strength. Mock-interview script you can run with a friend or with the implementation playbook.

Module 12. The first 90 days as a junior business analyst

What to do in the first 90 days of the BA seat so the role sticks. The seven stakeholders to introduce yourself to in week one. The dataset audit that every new BA should run in their first month. The four analyses you should ship in the first 60 days to earn trust. The career conversation to have at day 90 to set up the path to senior analyst. The course pays for itself when the role sticks, not when the offer arrives.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

Module 1 maps to the job descriptions sitting in your bookmarks bar right now.

Modules 2 through 7 produce the four artefacts that go on the public portfolio page.

Modules 8 through 10 are the packaging layer that gets the artefacts in front of recruiters.

Modules 11 and 12 are the conversion layer, interview to offer and offer to retained seat.

What you get with this course

Twelve written modules in the Art of Service learning environment, each with downloadable worked examples and templates.
Realistic customer-service ticket dataset for the SQL and pandas modules, with a clean schema and ready-to-run starter queries.
Cohort analysis notebook template, regression notebook template, and dashboard starter file you fork and adapt.
Portfolio page starter built in GitHub Pages so you can publish on the same weekend you finish the course.
Resume and LinkedIn profile templates written in BA vocabulary, with a checklist for the rewrite.
Hand-built implementation playbook tailored to your three current roles and the BA positions you are applying to.
30-day money-back guarantee.

What you will have in hand by Day 1, Week 1, Month 1

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

Modules 1 through 4 are typical first-week work and produce the first hero portfolio artefact.

Modules 5 through 8 complete the four hero artefacts and publish the portfolio page in the second week.

Modules 9 and 10 are the resume and LinkedIn rewrite, typical of the third weekend.

Modules 11 and 12 are the interview and first-90-days layer, used as needed when the application cycle turns into interviews.

Before and after

Before

Your LinkedIn headline says transitioning into business analytics. The recruiter who sees it skims past because there is nothing to click and no proof attached. Applications go out, replies do not come back, and the operations role keeps consuming the weekend.

After

Your LinkedIn headline links to a portfolio page with four artefacts a hiring manager can scan in 30 seconds. The resume reads as a BA resume. The recruiter responds because the proof is now sitting in front of them, not implied. The interview round goes to SQL pair-coding and a case study you have already practised. The offer arrives because the operations experience is now the asset, not the gap.

What happens if you do not address this

Every month spent applying without portfolio evidence is a month the operations role keeps growing while the BA opportunity window narrows. Hiring managers index hard on demonstrated work, not on stated intent, and the gap between transitioning and transitioned is measured in artefacts shipped, not certifications collected.

Who it is for

An operations professional with two to six years of customer service, revenue support, or process improvement experience, actively applying to business analyst, data analyst, or revenue analyst roles. Comfortable in spreadsheets, has touched SQL or wants to, has not yet built a public portfolio. Tired of being passed over for candidates with a single bootcamp project and no real-world stakeholder experience.

Who this is NOT for. Not for someone already employed as a senior data analyst or data scientist. Not for someone who wants a research-heavy machine learning curriculum. Not for someone unwilling to do four small project builds during the course.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access. Self-paced. Reread any module as often as the application cycle requires.

Time investment. Roughly four to six hours per week for three to four weeks if you want the four hero artefacts published. Faster on a focused weekend. The interview-prep and first-90-days modules are referenced again at the point of need rather than read in sequence.

Why $199 is the right number

A six-month bootcamp at five thousand dollars produces one capstone project and a cohort certificate. A free YouTube playlist produces fragmented skills with no portfolio. A certification produces a line on the resume that says you took an exam. This course produces four portfolio artefacts, a published portfolio page, a rewritten resume, a rewritten LinkedIn, and a hand-built implementation playbook for your specific transition, for 199 USD.

FAQ

I have not written SQL in years. Is this course at the right level?

Yes. Module 2 starts from joins and builds up to the window-function patterns that come up in BA interview pair-coding. If you have ever written a VLOOKUP, you have the prerequisite mindset. If you have never written SQL at all, expect one extra evening of practice on module 2 before the rest of the course flows.

Will the portfolio artefacts use real data from my current role?

No. The dataset is a realistic synthetic customer-service ticket table built for the course, so nothing you publish exposes your employer. The implementation playbook then maps the artefact patterns back to your specific operations and revenue support experience so the resume and case studies are grounded in your actual work.

How does this differ from a Coursera or DataCamp BA path?

Those teach skills in isolation through hundreds of small exercises and end with a certificate, not a portfolio. This course is built backward from the four artefacts a hiring manager actually opens, so every module produces a piece of the portfolio rather than a quiz score.

What if I get to the end and still cannot land a BA role?

30-day money-back guarantee, no questions asked. Beyond that, the implementation playbook includes a 90-day application cadence and a list of seven hiring channels (referrals, BA Slack communities, niche job boards, recruiter outreach scripts) that out-perform general job-board applications for career changers.

Do I need to know Python before starting?

No. Module 3 teaches pandas from zero, assuming only the spreadsheet logic an operations professional already has. The notebook template makes the syntax learnable by adapting working code rather than writing from scratch.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.