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Power BIData AnalyticsA/B TestingData Visualization

Operations Analytics Dashboard

An enterprise-grade operations analytics platform built on Power BI, integrating A/B test statistical significance evaluation, conversion funnel attribution, and channel ROI analysis with 90-day real-time data refresh and self-serve drill-down.

6 min read
Interactive Demo
4 tech tags

Overview

Designed for product and operations teams, this dashboard consolidates scattered data sources (MySQL, event tracking, ad platforms) into a unified Power BI environment covering DAU/MAU trends, A/B experiment significance, user funnel analysis, and channel acquisition ROI — with parameterized slicers for self-serve exploration.

Key Features

01

A/B Experiment Dashboard

embedded confidence intervals and Z-test module, auto-flagging significance (p<0.05/p<0.01), eliminating gut-feel decisions

02

Conversion Funnel Attribution

7-step funnel visualization, breakdowns by channel/device/time period, pinpointing exact drop-off nodes

03

Channel ROI Matrix

aligns ad spend with LTV and CAC, visualizing marginal return curves per channel in real time

04

Automated Report Push

Power Automate delivers daily 9am summary reports to Teams channels, eliminating manual data pulls

05

Data Lineage Tracking

key metrics annotated with source references so non-technical stakeholders can verify calculation logic

Methodology

Data layer uses Python ETL (pandas + sqlalchemy) to clean and flatten multi-source data into Azure SQL wide tables; Power BI connects via DirectQuery for real-time freshness. A/B significance is computed in DAX with a two-proportion Z-test formula; funnel analysis uses Power BI waterfall charts and custom SVG visual plugins. Row-Level Security (RLS) controls per-team data access across the entire dashboard.

Tech Stack

Power BIPBI
Data AnalyticsDA
A/B TestingA/B
Data VisualizationVIZ

Project Info

Read time6 min
Live demoAvailable
FeaturedNo
Tags4
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Interactive Demo

A/B Test Significance Analyzer

Select an experiment to view confidence gauges, metric comparisons, and statistical significance results.

A/B Testing · Statistical Significance

Operations Analytics Dashboard

Full A/B experiment results: sample sizes, significance gauge, metric comparison, statistical significance and decision recommendations.

Checkout Flow Simplification

Reduce checkout steps from 4 to 2, remove mandatory registration

Control

24,830

users

Treatment

25,110

users

Duration

14

days

95%0.0%高度显著 / Highly Sig.

Metric Comparison

Payment Conv. Rate

Sig.
+40.6%+1.4ppp=<0.001
Control
3.42%
Treatment
4.81%

Cart Abandon Rate

Sig.
-20.0%-13.7ppp=<0.001
Control
68.4%
Treatment
54.7%

Completion Time (s)

Sig.
-38.7%-55.0sp=<0.001
Control
142s
Treatment
87s

ARPU (¥)

Sig.
+9.2%+4p=0.041
Control
38.2¥
Treatment
41.7¥

Conclusion & Decision

Statistical confidence 99.2%

Significant result: Payment conversion +40.6% (3.42% → 4.81%), cart abandonment -13.7pp, confidence 99.2%. Recommend immediate full rollout.