Vũ Kim Ngân

by | Nov 19, 2025

Chúc mừng bạn đã hoàn thành khóa học xuất sắc 🎉

Nâng tầm phân tích – Kết nối dữ liệu – Dẫn đầu quyết định

Khóa học "Master Analytical Thinking & Data Analysis with Power BI" tại MazHocData mang đến tư duy phân tích và kỹ năng Power BI thực chiến, sẵn sàng ứng dụng vào doanh nghiệp thực tế.

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PROJECT 01

CRM Dashboard

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The CRM Sales Analytics dataset contains 3,000 B2B sales records and multiple supporting dimensions, modeling the full sales pipeline from lead acquisition to customer conversion. It captures key attributes such as industry, deal value, sales agent performance, probability scoring, product type, and organization size. Learners can act as CRM/Sales Analysts to evaluate conversion rates, identify high-value segments, assess sales cycle efficiency, analyze agent performance, and uncover churn risks supporting data-driven decisions for improving sales strategy and revenue forecasting.

Skills Applied

 Clean, model, and analyze multi-stage CRM pipeline data to uncover conversion patterns, deal value drivers, and sales cycle insights
 Compare industry, region, product type, and agent performance using structured analytical frameworks to identify growth opportunities. 
 Build Power BI visuals to evaluate accuracy of probability scores, detect churn signals, and support strategic decision-making.
PROJECT 02

Marketing Analysis

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The Marketing Campaign Analytics dataset contains 9,900 records of digital ads run across Facebook, Instagram, and Pinterest in the UK. It includes campaign attributes, devices, geo locations, ad formats, and performance metrics such as impressions, clicks, CTR, conversions, spend, CPC, ROI, and profit. Learners can analyze channel efficiency, device behavior, geo-level performance, seasonal trends, engagement impact, and budget effectiveness. The dataset supports identifying ROI drivers, diagnosing diminishing returns, and generating insights to optimize marketing strategy and allocation.

Skills Applied

Clean, model, and analyze multi-channel marketing data to evaluate ROI, conversion efficiency, and spend–performance relationships.  
Compare channel, device, format, geo, and time-based patterns using MECE frameworks to isolate performance drivers and validate hypotheses.
Create presentation slides & apply storytelling to communicate findings and recommendations effectively.