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business analytics

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Dual-Track Product Journal
Dual-Track Product Journal
May 7, 2025 · Operations

Why Aggressive Replenishment Can Destroy Your Supply Chain—and How to Fix It

The article reveals how over‑eager replenishment creates supply‑chain avalanches, zombie inventory, and bullwhip effects, then offers a step‑by‑step resurrection guide with dynamic safety stock, data‑validation loops, and self‑healing mechanisms to restore healthy inventory flow.

business analyticsinventory managementoperations
0 likes · 5 min read
Why Aggressive Replenishment Can Destroy Your Supply Chain—and How to Fix It
Model Perspective
Model Perspective
Feb 12, 2025 · Fundamentals

Can You Really Predict the Future? Lessons from Data, Causality, and Forecasting

Using a year‑long revenue dataset from an online‑education firm, this article examines how description, causal explanation, and statistical modeling together reveal patterns, uncover underlying drivers, and highlight the limits and uncertainties of forecasting future performance.

business analyticscausal inferencedata analysis
0 likes · 7 min read
Can You Really Predict the Future? Lessons from Data, Causality, and Forecasting
Qunar Tech Salon
Qunar Tech Salon
Jul 2, 2024 · Artificial Intelligence

Comprehensive Attribution Analysis Methodology and Its Business Application

This article presents a detailed attribution analysis framework—including background research, a four‑step workflow, Bayesian causal detection, Simpson's paradox handling, and real‑world case studies—demonstrating how data‑driven insights can improve conversion rates and operational efficiency across multiple business lines.

Attribution AnalysisBayesian NetworkData Mining
0 likes · 15 min read
Comprehensive Attribution Analysis Methodology and Its Business Application
DataFunTalk
DataFunTalk
Feb 21, 2024 · Product Management

How to Become a Good Content Data Product Manager

This article outlines the definition, core competencies, evaluation standards, career pathways, and practical growth advice for content data product managers, using product‑centric analogies, a competency matrix, business‑type matching, and a Q&A session to guide both aspiring and current professionals.

Data Product ManagementMetrics Designbusiness analytics
0 likes · 14 min read
How to Become a Good Content Data Product Manager
DataFunTalk
DataFunTalk
Jan 30, 2024 · Product Management

Practical Application of a Metric System Management Dashboard in Kuaishou E‑commerce Data Operations

This presentation details the design, construction, and iteration of a management dashboard ("cockpit") for Kuaishou's e‑commerce data product team, covering data‑driven business logic, indicator design, product and interaction design, stability assurance, and common challenges with solutions, all aimed at improving business insight and decision‑making.

business analyticsdata productmanagement dashboard
0 likes · 15 min read
Practical Application of a Metric System Management Dashboard in Kuaishou E‑commerce Data Operations
DataFunSummit
DataFunSummit
Dec 20, 2023 · Artificial Intelligence

Building and Applying an Image Tagging System: Architecture, Tag Design, Algorithms, and Business Use Cases

This presentation by senior data mining manager Zhou Yuanwei of Qunar outlines the architecture of an image tagging platform, the construction of a comprehensive tagging system, common algorithmic tags, and real-world applications such as look‑alike marketing, A/B test efficiency analysis, and business attribution, helping audiences understand tag types, design considerations, and value‑driven use cases.

AB testingData Miningbusiness analytics
0 likes · 2 min read
Building and Applying an Image Tagging System: Architecture, Tag Design, Algorithms, and Business Use Cases
DataFunSummit
DataFunSummit
Dec 14, 2023 · Artificial Intelligence

Data Intelligence Driving Business Growth: Overview of CI, BI, and AI

This article presents a comprehensive overview of data intelligence as a catalyst for business growth, detailing the roles of Customer Intelligence (CI), Business Intelligence (BI), and Artificial Intelligence (AI) in enhancing data analysis, decision‑making, and user‑centric product development across various organizational functions.

Artificial IntelligenceBig DataCustomer Intelligence
0 likes · 12 min read
Data Intelligence Driving Business Growth: Overview of CI, BI, and AI
DataFunSummit
DataFunSummit
Nov 28, 2023 · Product Management

Practical Application of a Metric‑Based Management Cockpit in Kuaishou E‑commerce Data Operations

This article shares the design, construction, and iteration practices of a management cockpit for metric systems within Kuaishou's e‑commerce data product team, covering data‑driven business logic, product architecture, indicator design, visualization, stability assurance, and common challenges to guide effective business decision‑making.

business analyticsdata productmanagement cockpit
0 likes · 15 min read
Practical Application of a Metric‑Based Management Cockpit in Kuaishou E‑commerce Data Operations
Test Development Learning Exchange
Test Development Learning Exchange
Nov 27, 2023 · Fundamentals

Practical Data Sampling Techniques and Code Examples for Various Business Scenarios

This article presents ten real‑world business scenarios illustrating data sampling methods such as random, stratified, time‑window, sliding‑window, keyword, group, interval, click‑based, and weight‑based sampling, each accompanied by clear Python pandas code examples.

Pythonbusiness analyticsdata sampling
0 likes · 6 min read
Practical Data Sampling Techniques and Code Examples for Various Business Scenarios
Test Development Learning Exchange
Test Development Learning Exchange
Oct 10, 2023 · Artificial Intelligence

Feature Engineering Techniques for Various Business Scenarios with Python Code Examples

This article presents practical feature‑engineering methods for ten common business domains, explaining the purpose of each feature, the extraction technique, and providing ready‑to‑run Python code snippets to help build more accurate predictive models.

Feature Engineeringbusiness analyticsdata preprocessing
0 likes · 7 min read
Feature Engineering Techniques for Various Business Scenarios with Python Code Examples
DataFunSummit
DataFunSummit
Sep 26, 2023 · Big Data

Understanding and Building Data Indicator Systems: JD’s Practices and Methodologies

This article explains how JD constructs and applies data indicator systems, covering the definition of metrics, the distinction between metrics and tags, the role of indicator systems in the data pipeline, traffic metric design, OSM modeling, north‑star metrics, DuPont analysis, and standardization of metric definition and development.

Big DataOSM Modelbusiness analytics
0 likes · 17 min read
Understanding and Building Data Indicator Systems: JD’s Practices and Methodologies
Test Development Learning Exchange
Test Development Learning Exchange
Aug 19, 2023 · Artificial Intelligence

Regression Analysis Methods and Code Examples for Various Business Scenarios

This article provides comprehensive regression analysis methods and Python code examples for various business scenarios including e-commerce, market research, healthcare, finance, social media, HR, education, hospitality, marketing, and logistics.

OLS regressionPoisson regressionPython
0 likes · 6 min read
Regression Analysis Methods and Code Examples for Various Business Scenarios
DataFunSummit
DataFunSummit
Jul 10, 2023 · Artificial Intelligence

Applying Causal Inference to Business Improvement: Concepts, Methods, and Case Studies from Xiaohongshu

This article explains why causal inference is needed in data‑driven businesses, introduces its theoretical foundations from computer science, econometrics and statistics, and demonstrates how various causal modeling techniques can be used to boost user retention and content creation on the Xiaohongshu platform.

A/B testingbusiness analyticscausal inference
0 likes · 12 min read
Applying Causal Inference to Business Improvement: Concepts, Methods, and Case Studies from Xiaohongshu
Ctrip Technology
Ctrip Technology
Jun 15, 2023 · Fundamentals

Causal Inference Theory and Its Business Applications in Ctrip Train Ticket Operations

This article introduces the fundamental concepts and theoretical frameworks of causal inference, explains Rubin's potential outcomes and Pearl's causal graph models, and demonstrates their practical deployment through uplift modeling, propensity‑score matching, synthetic control, and regression‑discontinuity case studies within Ctrip's train ticket business.

business analyticscausal inferencepropensity score matching
0 likes · 15 min read
Causal Inference Theory and Its Business Applications in Ctrip Train Ticket Operations
DataFunTalk
DataFunTalk
May 2, 2023 · Fundamentals

Understanding the Importance and Practices of Indicator Management

This article explains why indicator management is essential for consistent data usage, outlines the three key benefits of unifying data language, production, and usage, and details the main components of an indicator management system, including business process indicatorization, standardization, and operationalization.

Metric Managementbusiness analyticsdata governance
0 likes · 8 min read
Understanding the Importance and Practices of Indicator Management
政采云技术
政采云技术
Feb 14, 2023 · Operations

Understanding and Building an Indicator System: Definitions, Lifecycle, and Productization

This article explains the concept of an indicator system, its lifecycle stages, the reasons for building one, detailed construction steps, naming conventions, modeling approaches, and how the system can be productized to support data‑driven business operations.

business analyticsindicator systemmetrics
0 likes · 13 min read
Understanding and Building an Indicator System: Definitions, Lifecycle, and Productization
DataFunTalk
DataFunTalk
Dec 4, 2022 · Artificial Intelligence

Key Insights on Causal Inference: Motivation, Applications, Challenges, and Links to A/B Testing, ML, and Deep Learning

This article summarizes the motivations behind causal inference, its typical business applications such as intelligent decision‑making and prediction, the practical challenges of validation and data, and its relationship with A/B testing, machine learning, and deep learning, providing a concise overview for newcomers.

AB testingbusiness analyticscausal inference
0 likes · 10 min read
Key Insights on Causal Inference: Motivation, Applications, Challenges, and Links to A/B Testing, ML, and Deep Learning
DataFunSummit
DataFunSummit
Jan 22, 2022 · Fundamentals

How to Build a Data Metric System: Purpose, Methodology, and Application

With economic slowdown, the article explains why a data metric system is essential for business growth, introduces the OSM model (Object, Strategy, Measure), outlines four steps to build the system, and discusses its practical use, problem diagnosis, and implementation through Q&A.

OSM Modelbusiness analyticsdata metrics
0 likes · 9 min read
How to Build a Data Metric System: Purpose, Methodology, and Application
DataFunTalk
DataFunTalk
Jan 4, 2022 · Fundamentals

How to Build a Data Metric System: Purpose, Construction Steps, and Practical Application

This article explains why a data metric system is essential for business growth, describes the OSM (Object‑Strategy‑Measure) model and four concrete steps to construct a metric system, and shows how to use it for diagnosis, factor analysis, and problem solving in real‑world scenarios.

KPIsOSM Modelbusiness analytics
0 likes · 11 min read
How to Build a Data Metric System: Purpose, Construction Steps, and Practical Application
DevOps
DevOps
Nov 22, 2021 · Fundamentals

Establishing Data Thinking for Enterprise Digital Transformation

The article explains how enterprises can achieve digital transformation by adopting a data‑driven mindset, describing the essence of data thinking, its benefits, common cognitive traps, and practical steps to cultivate data sensitivity, analysis, decision‑making, and communication skills across business and technical teams.

Digital Transformationbusiness analyticsdata mindset
0 likes · 20 min read
Establishing Data Thinking for Enterprise Digital Transformation