BestHub
Sign in
Tagged articles

Data Analysis

547 articles · Page 3 of 6
Data Thinking Notes
Data Thinking Notes
Jul 30, 2023 · Fundamentals

Why Data Analysis Is Essential for Product Success: Real-World Payment Case Studies

This article shares practical experience building a payment data analysis system from scratch, explaining why data analysis matters, outlining a five‑stage framework, detailing metric design, and presenting common analytical methods such as funnel, multi‑dimensional, trend, comparison, Pareto, and cross analysis to drive product decisions.

Business IntelligenceData Analysismetrics
0 likes · 26 min read
Why Data Analysis Is Essential for Product Success: Real-World Payment Case Studies
HomeTech
HomeTech
Jul 26, 2023 · Artificial Intelligence

Practical Implementation of ChatGPT Technology Products: Architecture, Prompt Engineering, and Future Challenges

This article explores the practical deployment of ChatGPT‑based products, detailing the model fundamentals, technical architecture, engineering‑focused prompt design, real‑world application scenarios, and the challenges of model generalization, resource consumption, data privacy, interpretability, and ethical considerations.

AI architectureChatGPTData Analysis
0 likes · 15 min read
Practical Implementation of ChatGPT Technology Products: Architecture, Prompt Engineering, and Future Challenges
DaTaobao Tech
DaTaobao Tech
Jul 19, 2023 · Operations

Data‑Driven Optimization of Taobao Logistics Experience: Problem Definition, Metric Design, and Strategy Implementation

The article details Taobao’s data‑driven approach to redesigning logistics information display and self‑service tickets—defining problems, preparing subjective and objective data, creating metrics, analyzing pain points, implementing timed soothing messages and proactive tickets, and showing through A/B tests reduced help volume and improved user satisfaction.

Data AnalysisProduct Strategylogistics
0 likes · 12 min read
Data‑Driven Optimization of Taobao Logistics Experience: Problem Definition, Metric Design, and Strategy Implementation
21CTO
21CTO
Jul 11, 2023 · Artificial Intelligence

Unlocking ChatGPT’s Code Interpreter: 10 Powerful Use Cases You Must Try

OpenAI’s newly released Code Interpreter plugin lets ChatGPT write, run, and test code, offering file handling, a built‑in Python environment with popular libraries, and a secure sandbox, while showcasing ten impressive tricks—from converting GIFs to MP4s to turning data into interactive webpages.

ChatGPTCode interpreterData Analysis
0 likes · 8 min read
Unlocking ChatGPT’s Code Interpreter: 10 Powerful Use Cases You Must Try
JD.com Experience Design Center
JD.com Experience Design Center
Jul 5, 2023 · Product Management

How Causal Inference Can Unlock High‑Impact Product Requirements

This article reviews a product‑manager’s end‑to‑end workflow for forecasting demand value and validating hypotheses, illustrating how Wallace’s scientific loop translates to business, and detailing causal‑inference techniques such as matching, DID, regression discontinuity, and instrumental variables with a real‑world case study.

Causal InferenceData Analysiseconometrics
0 likes · 17 min read
How Causal Inference Can Unlock High‑Impact Product Requirements
DataFunSummit
DataFunSummit
Jul 3, 2023 · Big Data

Avoiding Data Misuse: Case Studies on Invalid Data, Simpson’s Paradox, and Statistical Pitfalls

This article examines how data can be misused or misinterpreted through real‑world case studies—ranging from breakfast myths and toothpaste advertising to contraceptive risks, crime statistics, judicial decisions, questionnaire bias, airline efficiency, and correlation‑causation confusion—offering practical guidelines to recognize and prevent invalid data analysis in the big‑data era.

BiasData AnalysisSimpson's paradox
0 likes · 22 min read
Avoiding Data Misuse: Case Studies on Invalid Data, Simpson’s Paradox, and Statistical Pitfalls
DeWu Technology
DeWu Technology
Jun 28, 2023 · R&D Management

Interpreting R&D Data Metrics: From Collection to Actionable Insights

Effective R&D efficiency improvement requires moving from manual, scattered, and unstandardized data collection to mature, integrated systems, defining metrics aligned with business goals, and applying a three‑layer framework—quantifiable, explainable, and intervenable—through cleaning, baseline setting, statistical analysis, root‑cause identification, and ROI‑focused action planning to turn numbers into actionable insights.

Data AnalysisR&D metricsdecision-making
0 likes · 12 min read
Interpreting R&D Data Metrics: From Collection to Actionable Insights
vivo Internet Technology
vivo Internet Technology
Jun 21, 2023 · Game Development

Post‑Darwin Method for Game Business Effect Evaluation Using Stratified Sampling

The paper presents the ‘Post‑Darwin’ evaluation framework, which uses stratified sampling to compare participants and non‑participants across uniform payment layers, overcoming uneven user distributions and the lack of viable A/B tests in game‑business effect analysis, and demonstrates its effectiveness through real‑world promotional and reservation case studies.

Business MetricsData AnalysisGame Analytics
0 likes · 13 min read
Post‑Darwin Method for Game Business Effect Evaluation Using Stratified Sampling
Python Programming Learning Circle
Python Programming Learning Circle
Jun 10, 2023 · Fundamentals

Advanced Pandas Operations: Complex Queries, Type Conversion, Sorting, Modification, Filtering, Iteration, and Function Application

This article provides a thorough walkthrough of advanced Pandas techniques—including complex logical queries, data‑type conversion, sorting, adding or modifying rows and columns, sophisticated filtering, iteration methods, and various function‑application utilities—complete with practical code examples for each operation.

Data AnalysisData manipulationFiltering
0 likes · 17 min read
Advanced Pandas Operations: Complex Queries, Type Conversion, Sorting, Modification, Filtering, Iteration, and Function Application
DaTaobao Tech
DaTaobao Tech
May 22, 2023 · Artificial Intelligence

Statistical and Machine Learning Metrics for Data Analysis

The article presents a practical toolbox of statistical and machine‑learning metrics—including short‑term growth rates, CAGR, Excel forecasting functions, Wilson score adjustment, sigmoid decay weighting, correlation coefficients, KL divergence, elbow detection with KneeLocator, entropy‑based weighting, PCA, and TF‑IDF—offering concise formulas and code snippets for data analysis without deep theory.

Data AnalysisPCAcorrelation
0 likes · 12 min read
Statistical and Machine Learning Metrics for Data Analysis
Python Crawling & Data Mining
Python Crawling & Data Mining
May 5, 2023 · Fundamentals

A Simple Pandas Trick to Check Columns and Assign Scores

In this article, the author shares a Pandas column‑checking solution, presents a concise code snippet that determines whether specific columns exist in each row and assigns scores accordingly, discusses encountered issues with the implementation, and offers practical tips for asking data‑analysis questions in Python communities.

Data AnalysisProgramming Tutorial
0 likes · 4 min read
A Simple Pandas Trick to Check Columns and Assign Scores
DataFunTalk
DataFunTalk
Apr 27, 2023 · Big Data

How to Build an E‑commerce Data Metric System

This article explains the concepts of good data metrics, how to identify and select appropriate indicators, and provides a step‑by‑step methodology—including the OSM model and a practical e‑commerce case study—for building a comprehensive data metric system that drives business growth.

Data AnalysisData MetricsKPI
0 likes · 15 min read
How to Build an E‑commerce Data Metric System
ITPUB
ITPUB
Apr 23, 2023 · Databases

Why SQL Still Dominates Data Analysis: From Relational Algebra to Modern OLAP

This article explains how SQL, built on relational algebra, became the standard analysis language for OLAP engines, covering its history, data models, syntax, functions, aggregation techniques, window functions, subqueries, and practical optimization considerations for modern data warehouses.

AggregationData AnalysisOLAP
0 likes · 46 min read
Why SQL Still Dominates Data Analysis: From Relational Algebra to Modern OLAP
58UXD
58UXD
Apr 14, 2023 · Fundamentals

Can ChatGPT Accurately Perform A/B Test Significance Checks? A Step‑by‑Step Guide

This article shows how to use ChatGPT to conduct statistical significance testing for A/B experiments, explains the underlying concepts of Type I and Type II errors, demonstrates a practical “spell” for conversion data, and provides a reliable online calculator for quick results.

A/B testingChatGPTData Analysis
0 likes · 6 min read
Can ChatGPT Accurately Perform A/B Test Significance Checks? A Step‑by‑Step Guide
DataFunSummit
DataFunSummit
Apr 14, 2023 · Big Data

An Overview of User Profiling: Definitions, Elements, Types, Dimensions, Applications, and Development Process

This article provides a comprehensive introduction to user profiling, covering its definition, key elements, classification types, common dimensions, practical application scenarios, lifecycle considerations, development workflow, and validation methods for building effective data‑driven user models.

Data Analysisbig datamarketing
0 likes · 10 min read
An Overview of User Profiling: Definitions, Elements, Types, Dimensions, Applications, and Development Process
Data Thinking Notes
Data Thinking Notes
Apr 9, 2023 · Big Data

Why Data Quality Is the Hidden Driver of Big Data Success

In the big‑data era, high‑quality data are essential for reliable analytics, and this article explains data‑quality concepts, key dimensions, analysis methods for missing values, outliers, inconsistencies and duplicates, as well as practical management practices to ensure data assets become a competitive advantage.

Data AnalysisData QualityETL
0 likes · 15 min read
Why Data Quality Is the Hidden Driver of Big Data Success
Laravel Tech Community
Laravel Tech Community
Apr 5, 2023 · Fundamentals

Pandas 1.5.3 Release Highlights: New Features, Bug Fixes, and Deprecations

Version 1.5.3 of the Python pandas library introduces optional pip extras, expanded Index support for NumPy dtypes, a new dtype_backend parameter, improved write copying, fixes for GroupBy cumulative operations overflow, several backward‑incompatible API changes, and multiple deprecations aimed at enhancing data analysis workflows.

Data AnalysisLibrarypandas
0 likes · 3 min read
Pandas 1.5.3 Release Highlights: New Features, Bug Fixes, and Deprecations
AntTech
AntTech
Mar 29, 2023 · Information Security

Introducing SCQL: Secure Collaborative Query Language for Privacy-Preserving Data Analysis

SCQL, an open‑source Secure Collaborative Query Language built on multi‑party computation, enables SQL‑style privacy‑preserving data analysis for small‑to‑medium organizations by offering easy integration, fine‑grained column‑level access control, broad data‑source support, and optimized performance for collaborative queries.

Data AnalysisPrivacy ComputingSCQL
0 likes · 6 min read
Introducing SCQL: Secure Collaborative Query Language for Privacy-Preserving Data Analysis
Ziru Technology
Ziru Technology
Mar 29, 2023 · Information Security

How Ziroom’s Risk Control Platform Detects and Prevents Account Fraud

This article outlines the background, risk scenarios, and technical design of Ziroom's risk control platform, describing how decision‑engine calculations, data‑driven feature extraction, and rule‑based strategies are used to identify and mitigate fraudulent account activities and reduce bad‑debt losses.

Data Analysisdecision enginefraud prevention
0 likes · 7 min read
How Ziroom’s Risk Control Platform Detects and Prevents Account Fraud
DataFunTalk
DataFunTalk
Mar 27, 2023 · Product Management

Metric System Analysis and Growth Practice: Building Indicator Systems, Designing Optimization Strategies, and Real-World Case Studies

This presentation explains how to construct a metric system, identify bottlenecks, design targeted growth strategies, and apply A/B testing through detailed examples from Volcengine's DataFinder and DataTester platforms, culminating in practical case studies from Douyin Group and other enterprises.

A/B testingData AnalysisIndicator System
0 likes · 15 min read
Metric System Analysis and Growth Practice: Building Indicator Systems, Designing Optimization Strategies, and Real-World Case Studies
Model Perspective
Model Perspective
Mar 12, 2023 · Fundamentals

Mastering the Entropy Weight Method: Theory, Steps, and Python Example

This article introduces the entropy weight method for multi‑criteria evaluation, explains its theoretical basis, outlines the calculation steps, presents a supplier‑selection case study, and provides a complete Python implementation to compute indicator weights and overall scores.

Data AnalysisMulti-criteria DecisionPython implementation
0 likes · 7 min read
Mastering the Entropy Weight Method: Theory, Steps, and Python Example
DataFunTalk
DataFunTalk
Feb 28, 2023 · Big Data

Data Analysis: Steps, Methods, and Thinking Frameworks

This article explains how to conduct data analysis by accurately interpreting numbers and context, objectively assessing problems with standards, selecting appropriate analytical methods, and adopting structured thinking frameworks such as business‑process, department‑function, and strategy‑goal orientations to derive actionable insights.

Business IntelligenceData Analysisanalysis framework
0 likes · 7 min read
Data Analysis: Steps, Methods, and Thinking Frameworks
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Feb 8, 2023 · Information Security

Exploring and Practicing Community Anti-Cheat Strategies at Xiaohongshu

The presentation outlines Xiaohongshu’s comprehensive community anti‑cheat strategy, defining cheating risks across industries, mapping the black‑gray ecosystem, and detailing a five‑module framework—risk perception, capability building, identification, mitigation, and evaluation—implemented via layered data architecture and multi‑stage detection to protect platform integrity.

Data Analysisanti-cheatfraud detection
0 likes · 17 min read
Exploring and Practicing Community Anti-Cheat Strategies at Xiaohongshu
Model Perspective
Model Perspective
Dec 30, 2022 · Fundamentals

How PCA Transforms Supplier Evaluation with Weighted Scores

This article explains the Principal Component Analysis (PCA) method, outlines its step‑by‑step weighting algorithm, and demonstrates a complete Python implementation that converts supplier metrics into objective scores using scikit‑learn.

Data AnalysisPCAPython
0 likes · 9 min read
How PCA Transforms Supplier Evaluation with Weighted Scores
Zhuanzhuan Tech
Zhuanzhuan Tech
Dec 28, 2022 · Product Management

A Comprehensive Guide to A/B Testing: System Design, Implementation, and Best Practices

This article explains the concept of A/B testing, details the architecture and implementation of an AB testing platform—including experiment, metric, whitelist, and traffic services—provides practical guidelines for experiment design, data reporting, statistical evaluation, and outlines future enhancements for product optimization.

Data Analysisproduct optimizationstatistical methods
0 likes · 20 min read
A Comprehensive Guide to A/B Testing: System Design, Implementation, and Best Practices
DataFunTalk
DataFunTalk
Dec 8, 2022 · Product Management

Improving New User Retention in a Video App through A/B Testing: A Case Study

This article presents a detailed case study of how a video app team used two rounds of A/B testing with different swipe‑up guide designs to diagnose retention issues, refine the user onboarding experience, and ultimately achieve significant improvements in new‑user retention and engagement metrics.

A/B testingData AnalysisMobile App
0 likes · 10 min read
Improving New User Retention in a Video App through A/B Testing: A Case Study
Model Perspective
Model Perspective
Dec 2, 2022 · Fundamentals

Master Linear Regression in R: From Random Data to Insightful Models

This article explains the theory behind simple linear regression, demonstrates how to generate random data and fit a model using R's lm() function, and interprets the statistical output including coefficients, significance tests, and goodness‑of‑fit measures.

Data AnalysisLinear RegressionR
0 likes · 4 min read
Master Linear Regression in R: From Random Data to Insightful Models
Model Perspective
Model Perspective
Nov 30, 2022 · Fundamentals

How to Perform One‑Sample and Two‑Sample t‑Tests in R

This article explains the theory behind hypothesis testing, demonstrates one‑sample and two‑sample t‑tests using R’s t.test() function with agricultural yield examples, and shows how to interpret one‑sided versus two‑sided test results for decision making.

Data AnalysisRhypothesis testing
0 likes · 5 min read
How to Perform One‑Sample and Two‑Sample t‑Tests in R
Model Perspective
Model Perspective
Nov 29, 2022 · Fundamentals

Mastering Probability Distributions in R: From Normal to Poisson

This article explains how various continuous and discrete probability distributions—such as normal, binomial, Poisson, and negative binomial—are used in real‑world contexts, introduces R’s naming conventions for distribution functions, and provides code examples for computing densities, CDFs, quantiles, and random samples.

Data AnalysisDistributionsR
0 likes · 5 min read
Mastering Probability Distributions in R: From Normal to Poisson
Model Perspective
Model Perspective
Nov 27, 2022 · Fundamentals

Mastering R Packages: Installation, Loading, and Usage Made Simple

This guide explains how to install, update, load, and use R packages—including CRAN and Bioconductor sources—by demonstrating key commands such as install.packages(), BiocManager::install(), library(), and help(), while also covering library paths and package management best practices.

BioconductorData AnalysisInstallation
0 likes · 4 min read
Mastering R Packages: Installation, Loading, and Usage Made Simple
Model Perspective
Model Perspective
Nov 12, 2022 · Fundamentals

Model-Centric Statistics: From Exploratory Analysis to Bayesian Inference

This article explains the fundamentals of statistics with a model‑centric approach, covering data collection, exploratory data analysis, descriptive statistics, visualization, and the three‑step Bayesian modeling process—including hypothesis formulation, model fitting, and evaluation—while emphasizing simplicity and practical programming tools such as Python.

Data Analysismodelingstatistics
0 likes · 6 min read
Model-Centric Statistics: From Exploratory Analysis to Bayesian Inference
Model Perspective
Model Perspective
Oct 31, 2022 · Fundamentals

Mastering the Method of Moments: Theory and Python Example

This article explains the method of moments for estimating population parameters, outlines its step‑by‑step derivation, and demonstrates a Python implementation that estimates a basketball player's shooting odds from binary outcome data using.

Data AnalysisParameter EstimationPython
0 likes · 4 min read
Mastering the Method of Moments: Theory and Python Example
DataFunSummit
DataFunSummit
Oct 28, 2022 · Big Data

Design and Practice of a Risk Control Experiment Platform at Du Xiaoman

The article introduces the business background, architectural design, evolution challenges, and step‑by‑step methodology for building and operating a risk‑control experiment platform that supports online and offline A/B testing, data analysis, and strategy iteration in internet finance.

A/B testingData Analysisexperiment platform
0 likes · 12 min read
Design and Practice of a Risk Control Experiment Platform at Du Xiaoman
Model Perspective
Model Perspective
Oct 17, 2022 · Fundamentals

What Does the Global Hunger Index Reveal About India’s Hunger Crisis?

The article examines the Global Hunger Index’s methodology and recent ranking, highlighting India’s severe hunger classification, the index’s three‑step calculation process, and the broader significance of composite evaluation models for assessing nutrition, health, and development across nations.

Data AnalysisGlobal Hunger Indexnutrition
0 likes · 14 min read
What Does the Global Hunger Index Reveal About India’s Hunger Crisis?
Sohu Tech Products
Sohu Tech Products
Oct 12, 2022 · Big Data

Using GoPUP: A Python Library for Easy Access to Public Data APIs

This article introduces the GoPUP Python library, explains how to install it, demonstrates retrieving Weibo index data with code examples, shows how to visualize the results using Pandas, Jupyter and Matplotlib, and lists the wide range of public data APIs the library supports.

Data AnalysisJupyterPython
0 likes · 7 min read
Using GoPUP: A Python Library for Easy Access to Public Data APIs
DataFunSummit
DataFunSummit
Oct 10, 2022 · Big Data

2022 Open Source Big Data Heat Report – Project Overview, Methodology, and Findings

The 2022 Open Source Big Data Heat Report, jointly launched by the Open Atom Open Source Foundation, X‑Lab, and Alibaba Open Source Committee, analyzes GitHub and Jira data from 2015‑2022 to map heat values across big‑data project categories, publishes a list of 92 selected projects, and invites additional contributions before its official release at the 2022 Cloud Expo.

Data AnalysisReportproject classification
0 likes · 6 min read
2022 Open Source Big Data Heat Report – Project Overview, Methodology, and Findings
DaTaobao Tech
DaTaobao Tech
Oct 8, 2022 · Big Data

Excel Data Visualization and Analysis Techniques

The article guides readers through practical Excel functions—such as REPT, SUMPRODUCT, FREQUENCY, and text extraction—and advanced chart types like grouped bar, butterfly, and dual‑pie charts, while offering visualization best practices that prioritize clarity, efficient data processing, and effective communication of insights.

Data AnalysisData VisualizationExcel
0 likes · 7 min read
Excel Data Visualization and Analysis Techniques
Python Programming Learning Circle
Python Programming Learning Circle
Oct 7, 2022 · Artificial Intelligence

Analyzing WeChat Friend Data with Python: Gender, Avatar, Signature, and Location Insights

This article demonstrates how to use Python libraries such as itchat, jieba, matplotlib, snownlp, and TencentYoutuyun to retrieve WeChat friend information and perform data analysis on gender distribution, avatar usage, signature sentiment, and geographic location, presenting results with charts and word clouds.

Data AnalysisPythonSentiment Analysis
0 likes · 12 min read
Analyzing WeChat Friend Data with Python: Gender, Avatar, Signature, and Location Insights
DevOpsClub
DevOpsClub
Sep 13, 2022 · R&D Management

How DevMind Transforms R&D Efficiency with Scalable Metrics

This article outlines the DevMind system—a comprehensive, data‑driven framework that turns R&D efficiency measurement into an online, low‑threshold, scalable practice, covering four best‑practice pillars, technical architectures, product modules, and real‑world impact within large organizations.

Data AnalysisDevOpsR&D Efficiency
0 likes · 28 min read
How DevMind Transforms R&D Efficiency with Scalable Metrics
Model Perspective
Model Perspective
Sep 10, 2022 · Fundamentals

How to Determine Histogram Bin Count Using Sturges' Formula

This article explains how to calculate the number of bins for a frequency distribution histogram using Sturges' formula, illustrating the process with a sample of 50 data points where the maximum value is 980 and the minimum is 500, and shows how to derive the bin width.

Data AnalysisHistogramSturges formula
0 likes · 1 min read
How to Determine Histogram Bin Count Using Sturges' Formula
Model Perspective
Model Perspective
Sep 10, 2022 · Fundamentals

What Is Statistics? A Beginner’s Guide to Data Collection, Analysis, and Inference

This article introduces the fundamentals of statistics, covering its purpose, types, data collection methods, data organization steps, graphical representation, measures of central tendency and dispersion, probability concepts, parameter estimation, hypothesis testing, and the distinction between correlation and regression analysis.

Data Analysishypothesis testingprobability
0 likes · 11 min read
What Is Statistics? A Beginner’s Guide to Data Collection, Analysis, and Inference
21CTO
21CTO
Sep 4, 2022 · Databases

Why SQL Remains a Must‑Learn Skill in 2022: Top 5 Reasons

Despite the rise of newer data tools, SQL continues to dominate the developer landscape in 2022, offering universal applicability, high demand, strong career prospects, and a rich history that makes it an essential skill for data analysts, developers, and high‑paying tech roles.

CareerData AnalysisSQL
0 likes · 7 min read
Why SQL Remains a Must‑Learn Skill in 2022: Top 5 Reasons
Model Perspective
Model Perspective
Aug 31, 2022 · Fundamentals

How to Build a Watermelon Sweetness Dataset: From Field to Features

This article describes how the author collected a watermelon dataset, defined measurable features such as size, color, sugar content, seed count, and texture, and documented the process with photos, tables, and a brief discussion of data characteristics for future machine‑learning analysis.

Data Analysisdata collectionfeature engineering
0 likes · 12 min read
How to Build a Watermelon Sweetness Dataset: From Field to Features
Python Programming Learning Circle
Python Programming Learning Circle
Aug 31, 2022 · Fundamentals

Pandas Data Manipulation: Sorting, Selecting, Grouping, and Reshaping Techniques

This article provides a comprehensive, visual guide to essential Pandas operations—including sorting, column selection, grouping, multi‑aggregation, filtering, dropping, joining, merging, pivot tables, melting, stacking, unstacking, and index manipulation—illustrated with clear code examples for data analysis in Python.

Data AnalysisData manipulationPython
0 likes · 4 min read
Pandas Data Manipulation: Sorting, Selecting, Grouping, and Reshaping Techniques
Model Perspective
Model Perspective
Aug 24, 2022 · Fundamentals

Unlocking Data Insights: How Principal Component Analysis Simplifies Complex Variables

Principal Component Analysis (PCA) reduces high‑dimensional data to a few uncorrelated components by maximizing variance, enabling noise reduction, visualization, and efficient modeling, with practical steps—including data standardization, covariance matrix computation, eigenvalue extraction, and component selection—illustrated through a clothing‑size measurement case study.

Data AnalysisPCAdimensionality reduction
0 likes · 9 min read
Unlocking Data Insights: How Principal Component Analysis Simplifies Complex Variables
Model Perspective
Model Perspective
Aug 16, 2022 · Fundamentals

13 Essential Statistical Analysis Methods Every Researcher Should Know

This article outlines thirteen key statistical techniques—including descriptive and inferential methods, hypothesis testing, reliability analysis, contingency tables, regression, clustering, discriminant, factor, and time‑series analysis—explaining their purposes, assumptions, and typical applications for researchers and data analysts.

ClusteringData Analysishypothesis testing
0 likes · 25 min read
13 Essential Statistical Analysis Methods Every Researcher Should Know
网易UEDC
网易UEDC
Aug 10, 2022 · Product Management

How to Prove Your Design Solves Real Problems: A 5‑Step Framework

This article outlines a five‑step framework for designers to demonstrate that their solutions address genuine product and experience problems, using qualitative user research, quantitative data analysis, stakeholder alignment, KPI impact assessment, and iterative validation to build trust and effectiveness.

Data AnalysisKPIsdesign validation
0 likes · 9 min read
How to Prove Your Design Solves Real Problems: A 5‑Step Framework
Python Programming Learning Circle
Python Programming Learning Circle
Aug 9, 2022 · Big Data

Why Choose Python for Data Analysis? A Comprehensive Guide

This article explains why Python is an ideal language for data analysis, covering its simplicity, extensive libraries, compatibility with big‑data platforms, and a step‑by‑step workflow that includes data acquisition, storage, preprocessing, modeling, and visualization, while also highlighting useful tools and resources.

Data AnalysisPythonworkflow
0 likes · 6 min read
Why Choose Python for Data Analysis? A Comprehensive Guide
Past Memory Big Data
Past Memory Big Data
Aug 9, 2022 · Big Data

Master the Complete Big Data Ecosystem in One Article

This article provides a comprehensive overview of the big data ecosystem, detailing nine core technology categories—from data collection and storage to computation, analysis, scheduling, and underlying infrastructure—along with tool comparisons, selection guidelines to help readers quickly build a complete big data knowledge system.

Data AnalysisData StorageZooKeeper
0 likes · 12 min read
Master the Complete Big Data Ecosystem in One Article
Python Programming Learning Circle
Python Programming Learning Circle
Jul 30, 2022 · Backend Development

Python Web Scraping Tutorial: Crawling QDaily, Storing in SQLite, Analyzing Data and Generating a Word Cloud

This tutorial walks through building a simple Python web crawler for the QDaily website, covering target analysis, environment setup, SQLite database creation, data extraction with requests and BeautifulSoup, storing articles and comments, performing basic analysis, and visualizing results with a word cloud.

BeautifulSoupData AnalysisPython
0 likes · 6 min read
Python Web Scraping Tutorial: Crawling QDaily, Storing in SQLite, Analyzing Data and Generating a Word Cloud
21CTO
21CTO
Jul 27, 2022 · Databases

Master 10 Essential Advanced SQL Concepts for Data Professionals

This article presents ten crucial intermediate‑to‑advanced SQL techniques—including CTEs, recursive CTEs, temporary functions, CASE‑WHEN pivots, EXCEPT vs NOT IN, self‑joins, ranking window functions, delta calculations, cumulative sums, and date‑time manipulation—to help data professionals ace interview questions and write cleaner, more powerful queries.

CTEData AnalysisInterview Preparation
0 likes · 11 min read
Master 10 Essential Advanced SQL Concepts for Data Professionals
Alibaba Cloud Native
Alibaba Cloud Native
Jul 15, 2022 · Cloud Native

Boost Data Analysis and ETL with Alibaba Cloud Function Compute Async Tasks

This guide explains how to use Alibaba Cloud Function Compute asynchronous tasks for large‑scale data analysis, database autonomous services, Kafka‑based ETL pipelines, and high‑performance video transcoding, highlighting architecture migration, cost reduction, deployment steps, and observable serverless task capabilities.

Data AnalysisETLServerless
0 likes · 16 min read
Boost Data Analysis and ETL with Alibaba Cloud Function Compute Async Tasks
Python Crawling & Data Mining
Python Crawling & Data Mining
Jul 14, 2022 · Fundamentals

How to Quickly Get Month Start and End Dates with Pandas

This tutorial demonstrates multiple pandas techniques—including datetime mapping, MonthBegin/MonthEnd offsets, floor operations, period conversion, and asfreq—to accurately retrieve the first and last day of a month for any given date, while highlighting common pitfalls and performance considerations.

Data AnalysisPythondatetime
0 likes · 7 min read
How to Quickly Get Month Start and End Dates with Pandas
Python Programming Learning Circle
Python Programming Learning Circle
Jul 13, 2022 · Fundamentals

Eight Useful Python Techniques for Data Analysis: List Comprehensions, Lambda, Map/Filter, NumPy arange/linspace, Pandas Axis, Concat/Merge/Join, Apply, and Pivot Tables

This article presents eight practical Python data‑analysis techniques—including one‑line list definitions, lambda expressions, map and filter functions, NumPy arange/linspace, Pandas axis handling, DataFrame concatenation/merging/joining, the apply method, and pivot tables—each illustrated with clear code examples and explanations.

Data AnalysisNumPyPython
0 likes · 7 min read
Eight Useful Python Techniques for Data Analysis: List Comprehensions, Lambda, Map/Filter, NumPy arange/linspace, Pandas Axis, Concat/Merge/Join, Apply, and Pivot Tables
Architecture Digest
Architecture Digest
Jul 12, 2022 · Big Data

Intelligent Gray Release Data System for Vivo Game Center: Methodology and Solutions

This article presents Vivo Game Center's end‑to‑end intelligent gray‑release data system, detailing its experimental mindset, statistical methods, data models, and product solutions that ensure scientific version evaluation, project progress, and rapid issue closure through root‑cause analysis and full‑process automation.

A/B testingData AnalysisGray Release
0 likes · 18 min read
Intelligent Gray Release Data System for Vivo Game Center: Methodology and Solutions
Python Crawling & Data Mining
Python Crawling & Data Mining
Jun 7, 2022 · Fundamentals

Compute Cumulative Sums and Build Stacked Charts with Pandas

This tutorial demonstrates how to generate random product usage data, compute per‑product usage‑duration percentages with pandas, calculate cumulative sums, and create a horizontal stacked bar chart using Matplotlib, offering multiple pandas techniques such as groupby‑value_counts, unstack, and crosstab for clear visual analysis.

Data AnalysisPythoncumulative sum
0 likes · 8 min read
Compute Cumulative Sums and Build Stacked Charts with Pandas
Python Programming Learning Circle
Python Programming Learning Circle
Jun 5, 2022 · Fundamentals

Pandas Data Manipulation: Sorting, Selecting, Grouping, and Reshaping

This article provides a visual guide to using Pandas for data manipulation, covering sorting with sort_values, column selection, grouping with groupby and various aggregations, filtering rows and columns, dropping, joining, merging, pivot tables, melting, stacking, unstacking, and index operations, illustrated with code snippets and screenshots.

Data AnalysisData manipulationPython
0 likes · 5 min read
Pandas Data Manipulation: Sorting, Selecting, Grouping, and Reshaping
Model Perspective
Model Perspective
May 30, 2022 · Fundamentals

Mastering Grey Relational Analysis: Step-by-Step Guide for Multi-Criteria Evaluation

This article outlines the complete procedure of Grey Relational Analysis, from preprocessing evaluation indicators and constructing the evaluation matrix to calculating relational coefficients, grey relational degrees, and ranking objects based on their relational scores, providing a clear framework for multi‑criteria decision making.

Data AnalysisDecision SupportEvaluation Method
0 likes · 3 min read
Mastering Grey Relational Analysis: Step-by-Step Guide for Multi-Criteria Evaluation
58UXD
58UXD
May 24, 2022 · Product Management

How to Turn Design Ideas into Data‑Driven Results: A Step‑by‑Step Guide

This article explains why designers must master data analysis, defines what “design data analysis” means, and walks through a three‑step framework—data splitting, tracking, and analysis—illustrated with practical e‑commerce and recruitment case studies to boost product metrics and retention.

A/B testingData AnalysisDesign
0 likes · 12 min read
How to Turn Design Ideas into Data‑Driven Results: A Step‑by‑Step Guide
DaTaobao Tech
DaTaobao Tech
Apr 29, 2022 · Industry Insights

How Taobao Mini Programs Cut Load Times by 30%: A Data‑Driven Performance Playbook

This article analyzes the performance challenges of Taobao Mini Programs, defines a multi‑dimensional experience metric, builds a standardized ops data pipeline, introduces the T2 first‑screen algorithm and a three‑stage performance model, and shares concrete optimization practices that reduced T2 from 2.7 s to 1.9 s while improving business metrics.

Data AnalysisOptimizationPerformance
0 likes · 10 min read
How Taobao Mini Programs Cut Load Times by 30%: A Data‑Driven Performance Playbook
Python Crawling & Data Mining
Python Crawling & Data Mining
Apr 27, 2022 · Fundamentals

Master Pandas: From CSV to Advanced Data Manipulation in Python

This comprehensive tutorial walks you through pandas fundamentals—including reading CSV/Excel files, creating Series and DataFrames, performing basic operations, cleaning data, indexing, grouping, concatenation, merging, and handling time series—using clear examples and code snippets.

Data AnalysisData manipulationdata cleaning
0 likes · 12 min read
Master Pandas: From CSV to Advanced Data Manipulation in Python
Python Crawling & Data Mining
Python Crawling & Data Mining
Apr 24, 2022 · Fundamentals

8 Powerful Pandas Tricks to Master Data Selection

This article presents eight practical pandas data‑selection techniques—including boolean indexing, loc/iloc, isin, str.contains, where/mask, query, filter, and any/all—illustrated with code examples and visual outputs to help Python users efficiently extract and analyze data.

Data AnalysisFilteringdata selection
0 likes · 9 min read
8 Powerful Pandas Tricks to Master Data Selection
Python Programming Learning Circle
Python Programming Learning Circle
Apr 12, 2022 · Fundamentals

Implementing Common Hypothesis Tests in Python: Z‑test, t‑test, F‑test and Data Exploration

This article demonstrates how to conduct various hypothesis tests—including Z‑test, one‑sample and two‑sample t‑tests, F‑test, as well as distribution fitting and outlier detection—using Python libraries such as Statsmodels, SciPy, and pandas on both the Iris dataset and a human temperature dataset.

Data AnalysisPythonZ-test
0 likes · 9 min read
Implementing Common Hypothesis Tests in Python: Z‑test, t‑test, F‑test and Data Exploration
HelloTech
HelloTech
Apr 11, 2022 · Artificial Intelligence

Precise Marketing Algorithm and Practice in HaLao

HaLao’s precise marketing system combines Pu‑Learning lookalike models, graph‑embedding user similarity analysis, and TSA/EM optimization within a robust feature‑engineering and deployment framework, delivering over 20% ROI gains and 3‑10× user growth while addressing low‑ROI and targeting inefficiencies.

AI in marketingData AnalysisMarketing Algorithms
0 likes · 9 min read
Precise Marketing Algorithm and Practice in HaLao
Shopee Tech Team
Shopee Tech Team
Apr 7, 2022 · Operations

MDAP: A Multi‑Dimensional Real‑Time Monitoring and Analysis Platform for Mobile Applications

MDAP is a multi‑dimensional real‑time monitoring platform for mobile apps that gathers metrics, logs, and traces via lightweight SDKs, processes data through micro‑service back‑ends using Flink, Spark, and ClickHouse, applies intelligent analysis for smoothness scoring, memory‑snapshot optimization, stack de‑obfuscation, crash clustering, and URL templating, and aims to extend end‑to‑end observability and predictive issue detection.

AIOpsData AnalysisPerformance
0 likes · 26 min read
MDAP: A Multi‑Dimensional Real‑Time Monitoring and Analysis Platform for Mobile Applications
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Apr 6, 2022 · Artificial Intelligence

Applying Data Analysis to Personal Wardrobe Optimization

By photographing and labeling every garment, the author uses data‑analysis metrics such as quantity and elimination rate to reveal seasonal imbalances, high discard rates for online and flashy items, and then recommends buying more denim, trying winter clothes in‑store, and regularly updating the wardrobe dataset.

Data Analysiscase studyfashion analytics
0 likes · 14 min read
Applying Data Analysis to Personal Wardrobe Optimization
Alibaba Terminal Technology
Alibaba Terminal Technology
Mar 31, 2022 · Frontend Development

Boosting Taobao Mini Program Performance: Key Lessons and Best Practices

This article examines how Taobao mini programs tackled stability and speed challenges by redefining user experience metrics, standardizing operational data, analyzing performance stages, and implementing best‑practice solutions such as engine reuse, data prefetching, and template snapshot rendering, resulting in measurable improvements.

Data AnalysisTaobaomini-program
0 likes · 9 min read
Boosting Taobao Mini Program Performance: Key Lessons and Best Practices
Python Crawling & Data Mining
Python Crawling & Data Mining
Mar 20, 2022 · Operations

Why Your Data Analysis Fails Without Business Context: A Food Store Case Study

Data analysis must be tightly linked to business needs, as illustrated by a Pareto analysis of a food specialty store that reveals a 55% user contribution to 80% sales, prompting strategic decisions on customer segmentation, value distribution, and growth tactics beyond traditional 20/80 expectations.

Customer SegmentationData AnalysisPareto principle
0 likes · 8 min read
Why Your Data Analysis Fails Without Business Context: A Food Store Case Study
Python Crawling & Data Mining
Python Crawling & Data Mining
Mar 12, 2022 · Fundamentals

From Raw Data to Actionable Insight: Master the 3 Recommendation Stages

This article explains the three progressive stages—giving data, giving conclusions, and giving viewpoints—that data analysts should follow to turn raw metrics into actionable business recommendations, and highlights common pitfalls such as unclear objectives, vague advice, and unimplementable suggestions, offering practical guidance for developing a data‑thinking mindset.

Data Analysisanalytics workflowbusiness insights
0 likes · 12 min read
From Raw Data to Actionable Insight: Master the 3 Recommendation Stages
DataFunSummit
DataFunSummit
Mar 11, 2022 · Fundamentals

Technical Growth Mindset: Essential Thinking Modes for Engineers

The article outlines a comprehensive technical growth mindset for engineers, describing seven progressive thinking modes—problem, tool, product, data, risk, production‑relationship, and craftsmanship/evangelism—plus brand and team mindsets, emphasizing lifelong learning and systematic self‑development.

Data AnalysisSoftware Engineeringgrowth mindset
0 likes · 17 min read
Technical Growth Mindset: Essential Thinking Modes for Engineers