INDEPENDENT LEARNING FROM FAR BUILD

Workplace project

Build a data analytics portfolio with a guided Far Build project in SQL, Python and Power BI. This is an independent workplace project, not a university course.

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Hands-on portfolio workAssessed by Far BuildPersonal guidance

A FAR BUILD PORTFOLIO PROJECT

Fintech and Digital Retail Data Analytics Capstone

Investigate sales records and buy now, pay later (BNPL) repayment risk for a fictional Egyptian electronics retailer. Connect Oracle SQL/PLSQL, Python with Pandas, and Power BI in one practical project.

$70 USDProject price28 daysFrom confirmed enrollment6–8 hoursPlanned study per week

Project overview
Project detail	Information
Project format	Hands-on, milestone-based capstone with guided steps, hints, starter templates, and a data dictionary.
Project provider	Far Build Online Courses.
Business scenario	Investigate differences between retail orders and finance ledger postings, then analyze BNPL repayment risk. The data contains potential exceptions; it does not establish a realized loss.
Who it is for	Aspiring data analysts and business, finance, or technology professionals exploring fintech, ecommerce, or digital retail analytics.
Entry requirements	Basic exposure to SQL, Python, or Power BI through an introductory course, bootcamp, or tutorial; comfortable computer and browser use; logical problem-solving.
Tools	Oracle SQL/PLSQL, Python and Pandas, and Power BI Desktop.
Weekly commitment	Plan for 6–8 hours per week.
Duration	Designed for four weeks at your own pace.
Price	$70 USD
Data note	All records are synthetic. Amounts are exercise values in USD, not live Egyptian market prices or exchange-rate conversions.

FOUR CONNECTED MILESTONES

Guided project phases

Use guided steps, hints, starter templates and a data dictionary. Submit the analysis files and short presentation described in your assignment.

Scroll sideways on smaller screens to compare the phases and portfolio outputs.

Milestones and portfolio outputs
Phase	What you will do	Portfolio output
1. SQL data reconciliation	Compare retail order totals with SALE_BOOKING ledger entries. Preserve unmatched records, investigate discrepancies, and document evidence-supported data repairs.	SQL analysis, reconciliation export, data-quality log, and explanation of key decisions.
2. Python and Pandas analysis	Clean the supplied data and examine sales by month, channel, city, and product category. Calculate repayment balances and default measures at the fixed reporting snapshot.	Executed notebook, cleaned analytical exports, reproducible cleaning log, findings, and stated limitations.
3. Power BI dashboard	Build a report for sales, reconciliation exceptions, and BNPL repayment risk. Define KPI denominators and check filters against the SQL and Python results.	Power BI report with six headline KPIs, charts, exception details, and clearly scoped filters.
4. Five-minute portfolio presentation	Explain your approach, one exception, one dashboard filter, your recommendations, and the limitations of the data.	A short screen-and-voice video and written executive summary. Publishing to GitHub or LinkedIn is optional.

All records are synthetic. Amounts are exercise values in USD, not live Egyptian prices or exchange-rate conversions. Potential exceptions in the data do not establish a realized loss.

PRACTISE. EXPLAIN. BUILD.

What you will gain

Ask about the $70 project

Portfolio project

A multi-phase project that you can adapt for your portfolio.

Applied analytics practice

Practice connecting SQL reconciliation, Python analysis, dashboarding, and business recommendations.

Assessment and feedback

Your submitted work is assessed against the project’s 100-point rubric, with feedback on strengths and areas to improve.

Certificate of Achievement

Learners who pass the final assessment receive a Certificate of Achievement issued by Far Build Online Courses. Your work is assessed against a 100-point rubric. The passing requirements and expected review timeline will be explained in your project materials before purchase.

Enrollment and submission

After your intake form and payment are confirmed, materials are sent within 24–48 hours. Your project runs for 28 calendar days from the enrollment date in your confirmation email. One resubmission is included if needed, by the deadline stated in your feedback.

Submit using a GitHub repository link unless your instructions offer another method. Publishing your presentation on GitHub or LinkedIn is optional. Ask about a private or alternative submission before sharing sensitive information.

Review our Terms of Service and Privacy Policy for assessment, refunds, original work and certificate verification.

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