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JD Cloud Developers
JD Cloud Developers
Sep 30, 2024 · Artificial Intelligence

How a Large‑Model Powered Bot Boosts Logistics Ops with Smart Q&A and Data Insights

This article describes the design, implementation, and impact of a large‑model‑driven logistics chatbot that unifies knowledge Q&A, data analysis, proactive alerts, and report pushing to streamline operations for functional staff, frontline workers, and managers, dramatically reducing query time and improving decision efficiency.

AI chatbotEnterprise AIKnowledge Base
0 likes · 20 min read
How a Large‑Model Powered Bot Boosts Logistics Ops with Smart Q&A and Data Insights
JD Tech Talk
JD Tech Talk
Sep 30, 2024 · Artificial Intelligence

Yunli XiaoZhi: An AI‑Powered Intelligent Assistant for Knowledge Q&A and Data Analysis in Logistics Operations

The document describes the design, implementation, and operational results of Yunli XiaoZhi, an AI‑driven portable knowledge‑base and data‑analysis chatbot that consolidates SOPs, manuals, and real‑time information for logistics staff, using LangChain‑based RAG, vector databases, and large‑model prompting to improve query efficiency, proactive alerts, and reporting across multiple user groups.

AIChatbotKnowledge Base
0 likes · 19 min read
Yunli XiaoZhi: An AI‑Powered Intelligent Assistant for Knowledge Q&A and Data Analysis in Logistics Operations
dbaplus Community
dbaplus Community
Sep 9, 2024 · Databases

Why SQLite Powers Billions of Devices: Real-World Use Cases Explained

SQLite, the lightweight embedded SQL engine created in 2000, is the world’s most deployed database, powering mobile apps, embedded systems, desktop software, data analysis tasks, and even browser‑based acceleration via WebAssembly, thanks to its zero‑configuration design and broad language support.

Embedded DatabaseMobile DevelopmentSQLite
0 likes · 8 min read
Why SQLite Powers Billions of Devices: Real-World Use Cases Explained
Java Tech Enthusiast
Java Tech Enthusiast
Sep 2, 2024 · Databases

Understanding SQLite: Usage Scenarios and Advantages

SQLite, a lightweight serverless relational database written in C, powers billions of devices and is used for mobile app storage, embedded systems, offline desktop applications, small‑to‑medium data analysis, and browser‑based acceleration via WebAssembly, supporting languages such as C, C++, Java, Python, and Swift.

Embedded DatabaseIoTSQLite
0 likes · 5 min read
Understanding SQLite: Usage Scenarios and Advantages
58UXD
58UXD
Aug 21, 2024 · Product Management

How Redesigning a Recruitment Platform Boosted User Engagement and Conversion

This case study details how a recruitment platform identified user‑experience gaps, used journey‑mapping to uncover blue‑collar preferences, implemented design strategies such as local‑job emphasis, anti‑spam features, and address filtering, and achieved measurable improvements in click‑through and conversion rates.

UX designdata analysisdesign strategy
0 likes · 9 min read
How Redesigning a Recruitment Platform Boosted User Engagement and Conversion
Test Development Learning Exchange
Test Development Learning Exchange
Aug 16, 2024 · Fundamentals

Advanced Pandas Techniques: Grouping, Aggregation, Window Functions, and More

This article demonstrates eleven practical Pandas examples covering grouping aggregation, conditional filtering, rolling windows, multi-indexing, melting, broadcasting, concatenation, merging, time-series creation, missing-value handling, and custom function application, each accompanied by complete Python code and expected output.

aggregationdata analysisdata manipulation
0 likes · 7 min read
Advanced Pandas Techniques: Grouping, Aggregation, Window Functions, and More
21CTO
21CTO
Aug 13, 2024 · Fundamentals

7 Must‑Know Open‑Source Python Projects Every Developer Should Explore

This article introduces seven noteworthy open‑source Python repositories—including Pandas, Apache Airflow, G4F, Scrapy, Ultroid, Zulip, and Freqtrade—highlighting their key features, typical use cases, and where to find them, offering developers a curated guide to valuable tools for data analysis, workflow automation, web crawling, chat bots, team collaboration, and crypto trading.

AutomationPythondata analysis
0 likes · 5 min read
7 Must‑Know Open‑Source Python Projects Every Developer Should Explore
Data Thinking Notes
Data Thinking Notes
Aug 8, 2024 · Fundamentals

How to Pinpoint the Real Drivers Behind Metric Fluctuations: Methods & Case Studies

This article explains the fundamentals of metric attribution, outlines a three‑step framework for identifying, analyzing, and solving metric changes, compares deterministic, probabilistic, and speculative methods, and illustrates the approach with two real‑world case studies using decomposition and machine‑learning techniques.

business metricscausal inferencedata analysis
0 likes · 16 min read
How to Pinpoint the Real Drivers Behind Metric Fluctuations: Methods & Case Studies
Python Programming Learning Circle
Python Programming Learning Circle
Jul 17, 2024 · Fundamentals

Seven Essential Python Efficiency Tools for Developers

This article introduces seven powerful Python libraries—Pandas, Selenium, Flask, Scrapy, Requests, Faker, and Pillow—explaining their core features, typical use cases, and providing ready‑to‑run code snippets to help developers boost productivity and automate routine tasks.

AutomationPythonWeb Scraping
0 likes · 6 min read
Seven Essential Python Efficiency Tools for Developers
DataFunTalk
DataFunTalk
Jul 13, 2024 · Artificial Intelligence

Metric Attribution in Internet Platforms: Concepts, Methods, and Case Studies

This article explains metric attribution for internet platforms, covering its definition, a three‑step framework, basic deterministic and probabilistic methods—including indicator decomposition, machine‑learning and SHAP techniques—illustrated with two detailed case studies and a brief overview of supporting tools.

Internet PlatformsSHAPdata analysis
0 likes · 15 min read
Metric Attribution in Internet Platforms: Concepts, Methods, and Case Studies
Python Programming Learning Circle
Python Programming Learning Circle
Jul 11, 2024 · Fundamentals

Critical Review of Python in Excel: Limitations, Use Cases, and Recommendations

The article provides a detailed technical analysis of Microsoft’s preview‑only Python in Excel feature, outlining its current capabilities, major limitations such as lack of VBA replacement, restricted package usage, cloud‑dependency, and workflow friction, while suggesting improvements and alternative approaches for data‑centric users.

AutomationAzureExcel
0 likes · 16 min read
Critical Review of Python in Excel: Limitations, Use Cases, and Recommendations
Python Programming Learning Circle
Python Programming Learning Circle
Jul 10, 2024 · Big Data

Using the TransBigData Python Library for Mobile Signaling Data Processing, Analysis, and Visualization

This article introduces the open‑source Python package TransBigData, explains how to install it, and demonstrates step‑by‑step methods for reading mobile signaling data, preprocessing, identifying stays and moves, extracting home and work locations, and visualizing individual activity patterns using Jupyter notebooks.

Big DataGeospatialPython
0 likes · 8 min read
Using the TransBigData Python Library for Mobile Signaling Data Processing, Analysis, and Visualization
NetEase LeiHuo UX Big Data Technology
NetEase LeiHuo UX Big Data Technology
Jun 21, 2024 · Game Development

Data-Driven Causal Analysis Methods for Game Updates When A/B Testing Is Not Feasible

When large‑scale A/B testing is impractical for high‑traffic, socially intensive games, developers can rely on methods such as Difference‑in‑Differences, hypothesis proportion analysis, and differential‑ratio comparison to infer the causal impact of content updates on key performance metrics.

Game AnalyticsGame DevelopmentHypothesis Proportion
0 likes · 7 min read
Data-Driven Causal Analysis Methods for Game Updates When A/B Testing Is Not Feasible
Test Development Learning Exchange
Test Development Learning Exchange
Jun 4, 2024 · Operations

HR Process Automation Scripts: Resume Parsing, Interview Emails, Pay‑Slip Generation, and Data Analysis

This article presents a collection of Python scripts that automate key HR tasks—including resume parsing, interview invitation emailing, pay‑slip creation, hiring‑channel analysis, turnover calculation, satisfaction survey reporting, salary competitiveness comparison, employee data updates, Word document generation, and leave‑request handling—complete with ready‑to‑run code examples.

AutomationEmailHR
0 likes · 10 min read
HR Process Automation Scripts: Resume Parsing, Interview Emails, Pay‑Slip Generation, and Data Analysis
DataFunSummit
DataFunSummit
May 22, 2024 · Artificial Intelligence

Optimizing Coupon Distribution with an Uplift Model

Data analyst Wu Weiwei from eBay China will present how uplift modeling—a causal inference technique—can be applied to e‑commerce coupon distribution, demonstrating methods to identify marketing‑sensitive users, optimize subsidy strategies, and improve business efficiency through data‑driven decision making.

E-commerce Marketingcoupon optimizationdata analysis
0 likes · 3 min read
Optimizing Coupon Distribution with an Uplift Model
Baidu MEUX
Baidu MEUX
May 8, 2024 · Big Data

Why KNIME Is a Powerful Open‑Source Solution for Big Data Analytics

In the data‑driven era, KNIME offers a free, visual, and highly scalable platform that streamlines massive data ingestion, preprocessing, analysis, automation, and visualization, enabling researchers to handle millions of records efficiently without extensive coding or costly software.

AutomationBig DataKNIME
0 likes · 9 min read
Why KNIME Is a Powerful Open‑Source Solution for Big Data Analytics
DataFunTalk
DataFunTalk
Apr 26, 2024 · Artificial Intelligence

Large Language Models in the Automotive Industry: Overview, Impact, and Practical Exploration

This article examines how large language models such as GPT and Transformer‑based architectures are reshaping the automotive sector by enhancing in‑vehicle intelligence, streamlining product development, improving customer service, and redefining data analyst roles, while also presenting practical experiments, deployment challenges, and future directions.

Automotive AIGPTLLM applications
0 likes · 18 min read
Large Language Models in the Automotive Industry: Overview, Impact, and Practical Exploration
JD.com Experience Design Center
JD.com Experience Design Center
Apr 19, 2024 · Product Management

How A/B Testing Transforms JD Express Mini‑Program Design: From Basics to Real‑World Results

This article explains why and how to conduct A/B testing for UI design, outlines experiment setup, variable creation, and data analysis, and presents detailed case studies of JD Express mini‑program pop‑up and order‑completion page experiments that demonstrate measurable improvements in click‑through and conversion rates.

A/B testingUX designdata analysis
0 likes · 18 min read
How A/B Testing Transforms JD Express Mini‑Program Design: From Basics to Real‑World Results
DaTaobao Tech
DaTaobao Tech
Mar 29, 2024 · Artificial Intelligence

Text-to-SQL with Large Language Models: DIN-SQL Approach

The DIN‑SQL approach enhances Text‑to‑SQL performance by using large language models in a decomposed in‑context learning framework with schema linking, query classification, SQL generation, and self‑correction modules, achieving state‑of‑the‑art 85.3% execution accuracy on the Spider benchmark by breaking complex queries into manageable sub‑tasks.

AI researchDatabase QueryingNLP
0 likes · 34 min read
Text-to-SQL with Large Language Models: DIN-SQL Approach
360 Quality & Efficiency
360 Quality & Efficiency
Mar 8, 2024 · Fundamentals

Using Python Pandas for Data Comparison Between Files and Databases

This article demonstrates how testers can ensure large‑scale data accuracy by leveraging Python’s Pandas library to compare and match data across files and databases, presenting a reusable class, field‑mapping techniques, code examples, and a comparison of Pandas with other data‑handling libraries.

CSVPythondata analysis
0 likes · 5 min read
Using Python Pandas for Data Comparison Between Files and Databases
DataFunSummit
DataFunSummit
Jan 24, 2024 · Big Data

Trends, Challenges, and Technical Practices of Modern Data Analysis and Indicator Platforms

This article reviews the evolution of data analysis and business intelligence, highlights current trends such as precision, agility, and real‑time needs, discusses common challenges, and presents the design and implementation of a unified semantic layer and indicator platform to enable agile, accurate, and real‑time analytics.

Big DataMetrics PlatformReal-time analytics
0 likes · 14 min read
Trends, Challenges, and Technical Practices of Modern Data Analysis and Indicator Platforms
Test Development Learning Exchange
Test Development Learning Exchange
Jan 16, 2024 · Artificial Intelligence

Python Code Samples for Data Scraping and Analysis Across Various Business Scenarios

This article presents a collection of Python code examples demonstrating how to scrape, process, visualize, and analyze data from news sites, social media, stock markets, e‑commerce, web traffic, text, images, and more, covering tasks such as clustering, time‑series forecasting, and sentiment analysis.

PythonWeb Scrapingdata analysis
0 likes · 12 min read
Python Code Samples for Data Scraping and Analysis Across Various Business Scenarios
Model Perspective
Model Perspective
Jan 2, 2024 · Fundamentals

How Empirical Research Transforms Knowledge: A Step‑by‑Step Guide

Empirical research, a systematic method that relies on real data and observation rather than theory alone, follows a clear process—from defining questions and hypotheses, collecting and cleaning data, selecting analysis techniques, to interpreting results and reporting findings—illustrated by the classic Pygmalion Effect study.

Pygmalion Effectdata analysisempirical research
0 likes · 6 min read
How Empirical Research Transforms Knowledge: A Step‑by‑Step Guide
DaTaobao Tech
DaTaobao Tech
Dec 22, 2023 · Big Data

AB Incremental Evaluation and Contamination Mitigation in Social Viral Experiments

The paper defines AB increment, shows how to calculate DAU gains from per‑user visit rates, explains how social viral experiments introduce unidirectional or bidirectional contamination that biases increment estimates, and proposes four probability‑estimation schemes—exponential smoothing, expansion coefficients, and homogeneous‑group sampling—to correct the bias based on experiment design and business context.

AB testingExperiment Evaluationcontamination
0 likes · 10 min read
AB Incremental Evaluation and Contamination Mitigation in Social Viral Experiments
Data Thinking Notes
Data Thinking Notes
Dec 21, 2023 · Product Management

Mastering Growth Metrics: Methodologies, Frameworks, and Real‑World Cases

This article explains Douyin’s growth‑analysis methodology, how to construct a comprehensive growth‑metric system with North‑Star indicators and hierarchical metric layers, the end‑to‑end analysis loop, new scenario‑driven metric applications, and a detailed case study on improving video‑submission rates.

AB testingGrowthdata analysis
0 likes · 24 min read
Mastering Growth Metrics: Methodologies, Frameworks, and Real‑World Cases
Data Thinking Notes
Data Thinking Notes
Dec 19, 2023 · Big Data

Mastering Data Analysis: Methodology, Team Building, and Career Insights

This comprehensive guide shares a seasoned data professional’s methodology, classifications, goal‑setting techniques, team‑building strategies, analyst competencies, report standards, and the three‑pillar "trend‑method‑technique" framework to help newcomers and veterans alike extract business value from data.

Business IntelligenceCareer DevelopmentMethodology
0 likes · 39 min read
Mastering Data Analysis: Methodology, Team Building, and Career Insights
Model Perspective
Model Perspective
Dec 19, 2023 · Fundamentals

Why Hospital Survival Rates Can Mislead: Unveiling Simpson’s Paradox

Simpson’s Paradox shows how aggregated data can suggest one trend while each subgroup reveals the opposite, illustrated with hospital survival rates where overall A appears better than B, yet detailed analysis by severity flips the conclusion, highlighting the need to consider background variables in statistical interpretation.

BiasSimpson's paradoxdata analysis
0 likes · 5 min read
Why Hospital Survival Rates Can Mislead: Unveiling Simpson’s Paradox
Huolala Tech
Huolala Tech
Dec 15, 2023 · Fundamentals

Do Mixed Fixed & Random Time‑Slice Schedules Shorten Experiment Recovery? Simulation Insights

This article analyses how fixed‑order and random‑order time‑slice carousel designs affect experiment interference, recovery cycles, and data homogeneity through theoretical discussion and extensive simulations, revealing that mixed scheduling rarely shortens cycles and may worsen homogeneity compared to pure fixed‑order approaches.

data analysisexperiment designfactorial design
0 likes · 9 min read
Do Mixed Fixed & Random Time‑Slice Schedules Shorten Experiment Recovery? Simulation Insights
Test Development Learning Exchange
Test Development Learning Exchange
Dec 10, 2023 · Backend Development

Online Traffic Replay in Python Automated Testing: Log Parsing, MySQL Storage, and Local Request Data Management

This article explains how to implement online traffic replay for Python automated testing by parsing logs, storing request data in a local MySQL database, analyzing user information with data‑analysis libraries, and locally persisting URL, method, headers, and body details using JSON files, complete with sample code.

Automated TestingPythondata analysis
0 likes · 5 min read
Online Traffic Replay in Python Automated Testing: Log Parsing, MySQL Storage, and Local Request Data Management
Tencent Cloud Developer
Tencent Cloud Developer
Dec 7, 2023 · Artificial Intelligence

Student Score Ranking and Distribution Analysis Using Python and Tencent Hunyuan Model

Using Tencent's Hunyuan model, the tutorial walks through a Python workflow that scrapes a student‑score table from a web page, saves it as CSV and Excel, cleans missing values, computes total and average scores, and visualizes their distributions with matplotlib, illustrating how LLMs can accelerate data‑analysis coding while still needing human verification.

Data visualizationMatplotlibPython
0 likes · 8 min read
Student Score Ranking and Distribution Analysis Using Python and Tencent Hunyuan Model
Python Programming Learning Circle
Python Programming Learning Circle
Nov 22, 2023 · Big Data

E‑commerce User Behavior Analysis and KPI Modeling with Python and SQL

This study analyzes JD e‑commerce operational data from February to April 2018, employing Python and SQL to compute key metrics such as PV, UV, conversion rates, attrition, purchase frequency, time‑based behavior, funnel analysis, retention, product sales, and RFM segmentation, and provides actionable recommendations for improving user engagement and sales performance.

RFMSQLdata analysis
0 likes · 30 min read
E‑commerce User Behavior Analysis and KPI Modeling with Python and SQL
Data Thinking Notes
Data Thinking Notes
Nov 21, 2023 · Operations

36 Essential Data Analysis Models Across 6 Business Domains

This article presents 36 concise data analysis models spanning six key business dimensions—Internet operations, strategy and organization, quality and production, marketing services, financial management, and human resources—to help analysts choose the right method for structured, logical, and effective insights.

Business AnalyticsMarketingOperations
0 likes · 12 min read
36 Essential Data Analysis Models Across 6 Business Domains
Model Perspective
Model Perspective
Nov 20, 2023 · Fundamentals

Mastering Math Modeling Competitions: Essential Skills, Tools, and Strategies

This guide answers the most frequent questions about math modeling contests, covering required knowledge, practical skill development, competition preparation tactics, Python and data‑analysis techniques, software choices, and recommended self‑learning resources, while also introducing a dedicated online course.

Modeling Toolscompetition preparationdata analysis
0 likes · 14 min read
Mastering Math Modeling Competitions: Essential Skills, Tools, and Strategies
DataFunTalk
DataFunTalk
Nov 3, 2023 · Product Management

Strategy Product Management: Principles, Frameworks, and Q&A for Content Recommendation

This article explains the role and mindset of a strategy product manager, outlines the decision‑making framework for content recommendation platforms, compares it with related positions, and answers practical questions about value, AI impact, commercial‑consumer trade‑offs, and content creation versus consumption.

AI ImpactRecommendation Systemscontent management
0 likes · 16 min read
Strategy Product Management: Principles, Frameworks, and Q&A for Content Recommendation
Test Development Learning Exchange
Test Development Learning Exchange
Oct 28, 2023 · Databases

How Data Analysis Improves User Experience: Methods and Practical SQL Code Examples

This article explains ten data‑analysis techniques for enhancing user experience—such as behavior tracking, A/B testing, sentiment analysis, and personalization—and provides concrete SQL code snippets that illustrate how to import, query, filter, sort, aggregate, join, update, delete, and back up data in relational databases.

A/B testingSQLUser experience
0 likes · 8 min read
How Data Analysis Improves User Experience: Methods and Practical SQL Code Examples
Data Thinking Notes
Data Thinking Notes
Oct 17, 2023 · Operations

How to Master Operational Data Analysis: From Metrics to Insightful Decisions

This guide explains how to build a comprehensive operational data analysis framework by adopting macro, business, thinking, and personal perspectives, defining dimensions and metrics, applying structured workflows, and avoiding common pitfalls to develop data sensitivity and drive effective decision‑making.

Business Intelligenceanalytics workflowdata analysis
0 likes · 12 min read
How to Master Operational Data Analysis: From Metrics to Insightful Decisions
Data Thinking Notes
Data Thinking Notes
Oct 8, 2023 · Product Management

How to Build a Robust Data Metric System for Business Success

This guide explains why many enterprises struggle with incomplete metric systems, outlines universal principles, methods, and step‑by‑step procedures—including defining a North Star metric, creating a metric dictionary, and systematic integration—to design effective, dynamic data indicator frameworks that drive informed decision‑making.

Business AnalyticsIndicator SystemNorth Star metric
0 likes · 12 min read
How to Build a Robust Data Metric System for Business Success
DataFunTalk
DataFunTalk
Sep 27, 2023 · Product Management

Building an AB Experiment System for User Growth Scenarios

This article presents a comprehensive AB testing framework tailored for new‑user growth scenarios, detailing the challenges of early traffic splitting, the design of a scientifically validated experiment system, ID selection criteria, and real‑world case studies that demonstrate improved retention and device activation.

AB testingdata analysismobile apps
0 likes · 12 min read
Building an AB Experiment System for User Growth Scenarios
Test Development Learning Exchange
Test Development Learning Exchange
Sep 24, 2023 · Artificial Intelligence

Common Python Libraries for Data Analysis, Summarization, and Classification

This article introduces five widely used Python libraries—Pandas, NumPy, NLTK, Scikit-learn, and Matplotlib—explaining their core functionalities for data cleaning, statistical analysis, natural language processing, machine‑learning modeling, and visualization, and provides practical code snippets for each.

MatplotlibNLTKNumPy
0 likes · 6 min read
Common Python Libraries for Data Analysis, Summarization, and Classification
DaTaobao Tech
DaTaobao Tech
Sep 20, 2023 · Big Data

Data-Driven Analysis of Taobao App Startup Performance

The article details Taobao’s data‑driven study linking user questionnaire satisfaction to cold‑start times, revealing that startup performance—especially on low‑end Android devices—dominates overall satisfaction, and proposes tier‑based cold‑start targets, a subjective‑objective model, and a monitoring pipeline to achieve a 20% satisfaction boost.

Startup TimeTaobaoUser experience
0 likes · 16 min read
Data-Driven Analysis of Taobao App Startup Performance
Test Development Learning Exchange
Test Development Learning Exchange
Sep 11, 2023 · Fundamentals

Why Do Data Analysis? 10 Practical Python Data Analysis Scenarios with Code Examples

The article explains the importance of data analysis for business insight, problem detection, decision support, operational optimization, forecasting, and competitiveness, and then presents ten practical Python code scenarios covering data loading, cleaning, filtering, aggregation, visualization, statistics, transformation, time‑series analysis, export, and machine‑learning applications.

Data ScienceData visualizationPython
0 likes · 7 min read
Why Do Data Analysis? 10 Practical Python Data Analysis Scenarios with Code Examples
php Courses
php Courses
Sep 7, 2023 · Backend Development

Using PHP for Data Analysis and Report Generation

This article explains how to use PHP to collect, process, and visualize data from sources such as CSV files, then design report templates and export the results as PDFs using libraries like Chart.js, PHPlot, TCPDF, and PHPExcel.

chartjsdata analysisreport-generation
0 likes · 6 min read
Using PHP for Data Analysis and Report Generation
Sohu Tech Products
Sohu Tech Products
Aug 23, 2023 · Backend Development

How to Scrape Bilibili Comments and Analyze Them with ChatGPT

This article walks through discovering Bilibili's comment API, programmatically fetching paginated JSON data, converting it into Java POJOs, storing and sorting the comments, and finally feeding the top entries to ChatGPT for automated sentiment and content analysis.

APIBilibiliChatGPT
0 likes · 14 min read
How to Scrape Bilibili Comments and Analyze Them with ChatGPT
Data Thinking Notes
Data Thinking Notes
Aug 21, 2023 · Product Management

How User Profiling Drives Personalized Marketing and Product Innovation

This article explains the fundamentals, principles, methodologies, and practical applications of user profiling, covering core concepts such as user characteristics, behavior, preferences, needs, and value, the data collection-to-model pipeline, common models like RFM, clustering, association rules, text mining, and how these insights enable personalized recommendation, precise marketing, brand management, service optimization, CRM, market research, and product innovation.

RFM modelSentiment Analysisassociation rules
0 likes · 14 min read
How User Profiling Drives Personalized Marketing and Product Innovation
JD Retail Technology
JD Retail Technology
Aug 21, 2023 · Artificial Intelligence

ChatGPT-4 Enhances Data Analysis Efficiency and Insight Across Big Data Scenarios

This article examines how ChatGPT-4, as an advanced natural‑language‑processing model, can streamline data analysis tasks—from generating Hive table definitions and sample data to crafting complex HiveSQL queries, visualizing results, and implementing ClickHouse and Flink solutions—thereby improving efficiency, insight, and problem‑solving in big‑data environments.

Big DataChatGPT-4ClickHouse
0 likes · 7 min read
ChatGPT-4 Enhances Data Analysis Efficiency and Insight Across Big Data Scenarios
Architect's Guide
Architect's Guide
Aug 21, 2023 · Fundamentals

Guidelines for Structured Data Analysis Reports and Effective Chart Usage

This article outlines a clear framework for writing data analysis reports—including hierarchical structure, concise conclusions, business‑oriented recommendations, reliable data sourcing, and best‑practice chart design—while highlighting common statistical pitfalls and tips for improving readability and impact.

Methodologybest practiceschart design
0 likes · 12 min read
Guidelines for Structured Data Analysis Reports and Effective Chart Usage
Model Perspective
Model Perspective
Aug 17, 2023 · Artificial Intelligence

Can Math Build the Ultimate Pokémon Dream Team? A Data‑Driven Analysis

This article uses a Kaggle Pokémon dataset of 802 creatures to explore statistical correlations, build a random‑forest classifier for legendary status, assess type strengths, and apply optimization techniques—including integer linear programming, greedy selection, and simulated annealing—to propose an optimal six‑Pokémon dream team.

data analysismachine learningoptimization
0 likes · 23 min read
Can Math Build the Ultimate Pokémon Dream Team? A Data‑Driven Analysis
DataFunTalk
DataFunTalk
Aug 12, 2023 · Big Data

Building an Agile, Real‑Time Data Analysis Platform with Unified Metrics

This article reviews the evolution and current challenges of modern data analysis, explains why metric‑driven approaches are needed, and details the design, core capabilities, and technical practices of a unified metric platform that enables agile, real‑time insights across diverse data sources.

agile datadata analysismetric platform
0 likes · 13 min read
Building an Agile, Real‑Time Data Analysis Platform with Unified Metrics
DataFunTalk
DataFunTalk
Aug 10, 2023 · Big Data

iQIYI Magic Mirror: Evolution of a Big Data Analysis Platform

The article details how iQIYI's Magic Mirror platform evolved from a simple single‑table reporting tool to a multi‑engine, self‑service big data analysis system that improves data access speed, reduces operational costs, and supports comprehensive business analytics across the company.

Data visualizationMagic Mirrorbig data platform
0 likes · 17 min read
iQIYI Magic Mirror: Evolution of a Big Data Analysis Platform
58 Tech
58 Tech
Aug 3, 2023 · R&D Management

Design and Implementation of Anjuke's R&D Efficiency Measurement System

This article describes Anjuke's R&D efficiency measurement framework, detailing its quality and efficiency metrics across project phases, the data collection and processing architecture, visualization dashboards, and analysis methods used to monitor and improve development productivity, reliability, and continuous delivery.

R&D managementSoftware qualitydata analysis
0 likes · 15 min read
Design and Implementation of Anjuke's R&D Efficiency Measurement System
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 ArchitectureChatGPTJava
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.

LogisticsUser experiencedata analysis
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.

AutomationChatGPTCode Interpreter
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.

BiasSimpson's paradoxdata analysis
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.

R&D metricsdata analysisdecision 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.

Game Analyticsbusiness metricsdata analysis
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.

PythonSortingdata analysis
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.

PCAcorrelationdata analysis
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.

Programming tutorialdata analysis
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.

KPIOSM modeldata analysis
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.

OLAPRelational AlgebraSQL
0 likes · 46 min read
Why SQL Still Dominates Data Analysis: From Relational Algebra to Modern OLAP
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.

Big DataMarketingRecommendation Systems
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.

Big DataData GovernanceData Management
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.

Librarydata analysispandas
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.

Privacy ComputingSCQLSQL
0 likes · 6 min read
Introducing SCQL: Secure Collaborative Query Language for Privacy-Preserving Data Analysis