Data Analyst
Builder Fellowship
From raw data to useful decisions. From learning to proof.
A practical, project-led journey. Build the core skills employers expect to see: spreadsheet analysis, SQL, Power BI, Python, statistics and the ability to explain what the data actually means.
A degree shows what you studied. Your work helps show what you can do.
GBD is not built around watching lessons and collecting certificates. It is built around learning, applying, getting feedback, improving, and demonstrating capability.
A Builder Mindset, Applied to Data
Data analysis is more than learning tools. A capable analyst can clarify a question, check whether the data is trustworthy, choose a sensible method, communicate what was found and identify what should happen next.
GRASP
Understand the foundations
Deconstruct data types, tidy schemas, relational query logic, and statistical distributions from first principles.
BOOST
Practise and fix gaps
Tackle complex join scenarios, write intricate DAX measures, audit data quality, and resolve edge-case errors.
DELIVER
Show work that can be reviewed
Publish code notebooks, interactive dashboards, and written executive findings that undergo rigorous evaluation.
EARN
Pursue opportunities with evidence
Walk interviewers through your live artifacts, defending your analytical logic with tangible proof of capability.
What You Should Be Able to Demonstrate
Clean and Inspect Datasets
Identify missing values, duplicates, and inconsistent data formats with repeatable verification procedures.
Multi-Table SQL Relational Queries
Write robust queries across multiple tables with CTEs, joins, and row-count checks to guarantee query accuracy.
Power BI Data Modeling & Dashboards
Build star-schema dimensional models, formulate custom DAX measures, and design intuitive visual hierarchy.
Python & Pandas Exploratory Analysis
Conduct repeatable data preparation and exploratory data analysis (EDA) documented in readable Jupyter notebooks.
Rigorous Statistical Reasoning
Apply statistics carefully, quantify variance with confidence intervals, and strictly distinguish correlation from causation.
Persuasive Stakeholder Communication
Explain insights, state assumptions and limitations transparently, and recommend actionable business next steps.
Who This Is For
College students, fresh graduates, and early-career learners who want a practical, no-nonsense starting point in analytics. No prior analytics experience is required. You should be willing to practise consistently, ask critical questions, and revise work based on feedback.
The Time Commitment
Plan for roughly 8–12 hours each week across live guided sessions, independent practice, and project deliverables. The cohort targets 12 weeks and may extend to 16 weeks if the evidence shows a learner needs more guided practice.
Core Skills You'll Master
Every skill in this curriculum is taught in the order it becomes useful in real business investigations. Click any skill to explore industry demand and market trajectory.
Target Career Paths
This fellowship qualifies you across commercial, operational, and product analytics roles. Click any career path to explore salary benchmarks and day-to-day responsibilities.
Tools Taught in the Order They Become Useful
12 weeks of progressive mastery, organized into two comprehensive parts. Each module ends with a visible, demonstrable piece of work.
Part I: Foundations First
Tools are taught in the order they become useful: Excel, SQL relational querying, and Power BI ETL.
Topics Covered
Data types; tidy data; sorting and filtering; formulas; IF and lookup functions; text/date functions; duplicates and missing values; pivot tables; charts; descriptive statistics; KPIs.
Spreadsheets remain the most widely used analytical tool in global business. Understanding tidy data principles and audit-ready formulas prevents errors before data is loaded into databases.
You will master structured data design, pivot aggregations, KPI summaries, and automated formula logic for immediate decision support.
Cleaned spreadsheet + analytical findings note detailing business anomalies.
Curriculum Rule
Each module ends with a visible piece of work. Learners move forward by demonstrating understanding—not simply by attending a session.
12 Weeks is the Target — Not a Race
The program may extend to week 16 when learners need extra practice, feedback or revision. The extension is for mastering the core and completing quality work—not for adding unrelated topics.
Case Studies & Portfolio Work
GBD uses practical datasets with clear business questions. Rather than collecting certificates, you leave with five demonstrable portfolio artifacts that prove your capability.
SPREADSHEET INVESTIGATION
Sales, Operations or Service Data
Clean the dataset, define metrics, use pivot tables and charts, and write three evidence-backed findings. Note data-quality issues.
SQL BUSINESS INVESTIGATION
Retail or E-Commerce Data
Use relational tables to investigate growth, product performance, customer segments or drop-offs. Submit readable queries and validation checks.
POWER BI DASHBOARD
Operations or Commercial Performance
Build a modelled dashboard with useful measures, filters and a clear narrative. Explain the intended audience and decisions supported.
PYTHON EDA NOTEBOOK
A Public Dataset with a Real Question
Prepare data with pandas, explore patterns, visualise results and document assumptions so another person can reproduce the work.
END-TO-END ANALYSIS
A Bounded Real-World Business Problem
Define the question, inspect and clean data, analyse it, visualise results, state limitations, recommend next steps and defend your decisions.
Retail and e-commerce • Customer behaviour & retention • Operations & logistics • Public datasets • Digital campaign measurement • Service performance
*The final datasets depend on licensing, access, and cohort needs. These are proposed learning projects, not claims of commercial employer partnerships.
Progress is Measured in Work
A polished dashboard is not enough if the numbers are wrong. Evaluation rewards correctness, reasoning, data quality, business relevance, communication and reproducibility.
Assessment Rubric & Weightings
Every submitted artifact is evaluated against these strict criteria.
Queries, calculations and visuals match the data. No join multiplication or formula errors.
Question and method make sense; interpretation follows evidence rather than speculation.
Missing values, duplicates, format inconsistencies and assumptions are systematically addressed.
Findings directly connect to a concrete decision, operational lever, or user need.
Clear writing, intuitive visual layout, and rigorous oral defense of decisions.
Readable files, documented SQL/Python logic, and traceable steps that another person can replicate.
What the Learning Loop Looks Like
LEARN
ConceptInteractive lectures on core analytical principles.
PRACTISE
ExerciseHands-on guided problem sets and syntax reps.
SUBMIT
EvidenceArtifacts uploaded to repository for review.
REVIEW
FeedbackDetailed mentor audit against the rubric.
REVISE
ImprovementResubmission to achieve verified mastery.
IMPORTANT: Attendance Alone is Not Proof of Skill
Expect exercises, reviews, corrections, resubmission and a project explanation. Any certificate reflects requirements actually completed. Job or internship outcomes are not guaranteed.
How GBD is Different
We reviewed the public course outlines and program pages of Meta, Google and Coding Ninjas, plus Microsoft learning resources. This is a curriculum/positioning comparison—not a claim that one provider is universally better.
Meta Data Analyst Certificate
CourseraSpreadsheets, SQL, Python/pandas, statistics, Tableau, data management and hands-on projects.
Adopt the broad workflow and practical projects; keep the short cohort focused on fewer core tools for deep mastery rather than surface familiarity.
Google Data Analytics Certificate
CourseraQuestion-led analysis, cleaning, analysis, visualisation, presentation and data ethics across a multi-course path.
Keep business questions, data quality, and oral communication threaded through every single week of the fellowship.
Coding Ninjas Data Analytics Bootcamp
BootcampExcel, SQL, Python, EDA, statistics, BI, AI-infused workflows, case studies, live support and career assistance; some versions include IBM/Microsoft credentials.
Use case-study-led design and explicit projects as inspiration. GBD’s differentiator is the small builder-fellowship philosophy—not claiming equivalent partners, credentials or placement support.
Microsoft Learn / Power BI
PL-300 & AzurePower BI data preparation, modelling, visualisation/analysis and management/security; Azure Fundamentals covers cloud concepts and services.
Make Power BI our primary enterprise BI tool and add concept-level cloud literacy. No Microsoft certification is implied.
Our Deliberate Trade-Off
A 12–16 week cohort cannot responsibly promise mastery of every tool and specialty. GBD prioritises Excel/Sheets, SQL, Power BI, Python/pandas, statistics, data quality and communication.
Your Work Should Speak For You
The aim is not to leave with a long list of tools on a resume. It is to leave with work you can walk someone through: the question, how you handled the data, why you chose your method, what you found and what you would do next.
Data Analyst Builder Fellowship
One Program Fee • Target 12 Weeks • Extendable to 16 Weeks
Before You Apply (Read Carefully)
Be ready to set aside around 8–12 hours each week for sessions and independent work.
Practise independently between guided sessions without relying solely on passive attendance.
Bring questions, thought-out attempts, and doubts—not just screenshots of completed tasks.
Be willing to receive honest feedback, accept rubric deductions, and revise your work.
Understand that a job or internship is not guaranteed; you are building demonstrable proof of skill.
Cohort dates, delivery format, mentor availability and support arrangements should be confirmed by GBD before enrollment. Delivery may adapt to student progress while keeping core outcomes intact.
Ready to Build Your Analytical Proof?
We do not accept passive enrollments. Admissions are processed through an intent-based interview to ensure you have the time and drive to complete the deliverables.