{"product_id":"139849","title":"Building Data Engineering Fundamentals for Data Analysts with Python ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/3jXOZ6jn52GiKUTM3CVXYtH4NK9uVj.png?v=1765076776\" style=\"max-width:100%;max-height:10px\"\u003e\u003c\/div\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\n\n\u003cdiv style=\"width:95%\"\u003e\n\n\u003cdiv style=\"text-align:center;font-size:30px;font-weight:bolder;line-height:1.6em\"\u003e Building Data Engineering Fundamentals for Data Analysts with Python \u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"border-bottom:1px;border-bottom-style:dotted;border-color:;padding-bottom:20px\"\u003e\u003ccenter\u003e\u003ctable align=\"center\" width=\"100%\"\u003e\u003ctbody style=\"border:0px\"\u003e\n\n\u003ctr\u003e\u003ctd align=\"center\" style=\"line-height:1.2em;text-align:center;font-size:18px;color:black;font-weight:bold;padding-bottom:20px;\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/image.yes24.com\/goods\/154230519\/XL\" style=\"max-width:100%;height:auto\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\u003c\/table\u003e\u003c\/center\u003e\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;{split_style6}padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e Description \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;word-break:break-all;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eBook Introduction\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003e\u003cdiv\u003e \"Data Engineering Fundamentals for Data Analysts with Python\" is a practical introductory book on data engineering for data analysts and job seekers.\u003cbr\u003e\u003cbr\u003e Focusing on the ETL (Extract, Transform, Load) process, which is the core of data engineering, it covers various technologies step by step, including Python, MySQL, Docker, MongoDB, DuckDB, Milvus, Streamlit, and FastAPI.\u003cbr\u003e\u003cbr\u003e The book has the following characteristics:\u003cbr\u003e - Starting with setting up the development environment: Covers Ubuntu development environment based on MacOS\/Windows, Git, Python, MySQL, and Docker. \u003cbr\u003e- Practical training throughout the entire ETL process: Extract data from various data sources such as CSV\/Excel\/JSONL\/Web Crawling\/API, convert it using Python and NumPy\/Pandas, and load it into MySQL\/NoSQL.\u003cbr\u003e - Multithreading and Optimization: Explains Python GIL limitations and bypass strategies, as well as parallel\/concurrent processing techniques, with actual code.\u003cbr\u003e - Database in-depth: Includes MySQL's main grammar, ERD design, partitioning, NoSQL comparison, and MongoDB utilization.\u003cbr\u003e - Practical Project: Experience building an end-to-end ETL pipeline that connects DuckDB and Milvus for vector search, Streamlit-based image search, and FastAPI web app development.\u003cbr\u003e\n\n\u003c\/div\u003e\u003c\/div\u003e\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e # Table of Contents\u003cbr\u003e\u003cbr\u003e Entering** ...................................................\u003cbr\u003e 10\u003cbr\u003e\u003cbr\u003e Chapter 1.\u003cbr\u003e Setting up the development environment (p.12)\u003cbr\u003e - Ubuntu 24.02 LTS development environment setup (MacOS) ...........\u003cbr\u003e 12\u003cbr\u003e - Setting up an Ubuntu 24.02 LTS development environment (Windows) .........\u003cbr\u003e 16\u003cbr\u003e - Port Forwarding ......................\u003cbr\u003e 17  \u003cbr\u003e- Setting up Git .................................................\u003cbr\u003e 20\u003cbr\u003e - Setting up Python development environment .............................\u003cbr\u003e 23\u003cbr\u003e - MySQL Installation and Basic Configuration ........................\u003cbr\u003e 28\u003cbr\u003e - Docker installation and configuration ............................\u003cbr\u003e 35\u003cbr\u003e\u003cbr\u003e Chapter 2. Basic Python Grammar for ETL (p.41)\u003cbr\u003e - ETL Overview .......................................\u003cbr\u003e 41\u003cbr\u003e - Why use Python for ETL? .................\u003cbr\u003e 42\u003cbr\u003e - Example 1: Collecting server log data ................\u003cbr\u003e 45\u003cbr\u003e - Example 2: Data extraction through API connection ............\u003cbr\u003e 46\u003cbr\u003e - Basic Python Grammar for Multithreading ..............\u003cbr\u003e 47\u003cbr\u003e\u003cbr\u003e Chapter 3.\u003cbr\u003e Python Multithreading (p.53)\u003cbr\u003e - Basics of thread creation and management ........................\u003cbr\u003e 54\u003cbr\u003e - Limitations of Python GIL and Parallel Processing ..................\u003cbr\u003e 61\u003cbr\u003e - GIL bypass and efficient parallel\/concurrent processing strategies........\u003cbr\u003e 62\u003cbr\u003e - Single process vs multi-process ..................\u003cbr\u003e 65\u003cbr\u003e\u003cbr\u003e Chapter 4.\u003cbr\u003e Data Extraction (p.71)\u003cbr\u003e - CSV file based data extraction ........................ \u003cbr\u003e71\u003cbr\u003e - Excel-based data extraction ...........................\u003cbr\u003e 84\u003cbr\u003e - JSONL based data extraction ..........................\u003cbr\u003e 92\u003cbr\u003e - Web Crawling (requests, BeautifulSoup) ..........\u003cbr\u003e 105\u003cbr\u003e - OpenWeatherMap API Crawling ..................\u003cbr\u003e 118\u003cbr\u003e - MySQL data collection ..............................\u003cbr\u003e 129\u003cbr\u003e\u003cbr\u003e Chapter 5.\u003cbr\u003e MySQL Key Grammar (p.144)\u003cbr\u003e - Exploring the core roles of MySQL ...........................\u003cbr\u003e 144\u003cbr\u003e - Introduction to MySQL Tutorial .................................\u003cbr\u003e 147\u003cbr\u003e - Create Sample Database ............................\u003cbr\u003e 148\u003cbr\u003e - ERD concept and utilization method ...........................\u003cbr\u003e 151\u003cbr\u003e - MySQL main grammar ................................\u003cbr\u003e 156\u003cbr\u003e - Partitioning of apartment transaction price data by year...\u003cbr\u003e 174\u003cbr\u003e - Efficient analysis using partitioned data ..........\u003cbr\u003e 179\u003cbr\u003e\u003cbr\u003e Chapter 6.\u003cbr\u003e Data Transformation (p.186)\u003cbr\u003e - String Data Processing ...........\u003cbr\u003e 188\u003cbr\u003e - Understanding and using regular expressions .......................\u003cbr\u003e 190\u003cbr\u003e - NumPy vectorization principles, necessity, and implementation ..................\u003cbr\u003e 196  \u003cbr\u003e- Analysis of Pandas and NumPy vectorization benchmarks ............\u003cbr\u003e 202\u003cbr\u003e - Handling missing values ​​using NumPy ........................\u003cbr\u003e 209\u003cbr\u003e - Data frame processing? Column transformation and type conversion...\u003cbr\u003e 231\u003cbr\u003e - Data frame processing? Date and time processing..........\u003cbr\u003e 243\u003cbr\u003e - Practical examples of handling time series data frames ............\u003cbr\u003e 265\u003cbr\u003e\u003cbr\u003e Chapter 7.\u003cbr\u003e Data Load (p.274)\u003cbr\u003e - The need for load in ETL ....................\u003cbr\u003e 274\u003cbr\u003e - Python meets databases ....................\u003cbr\u003e 275\u003cbr\u003e - Collection and processing of practical log data ....................\u003cbr\u003e 294\u003cbr\u003e - Storing MySQL log data in Parquet ...............\u003cbr\u003e 308\u003cbr\u003e - Comparative Analysis of NoSQL Databases ....................\u003cbr\u003e 312\u003cbr\u003e - Saving error logs using MongoDB ................\u003cbr\u003e 318\u003cbr\u003e\u003cbr\u003e Chapter 8. Practical Examples of Building ETL Pipelines and Vector Search (p.346)\u003cbr\u003e - Overall system overview ................................\u003cbr\u003e 346\u003cbr\u003e - Multi-database access .....................\u003cbr\u003e 347  \u003cbr\u003e- Key core technologies and roles ..........................\u003cbr\u003e 348\u003cbr\u003e - Data collection process (Extract) ........................\u003cbr\u003e 349\u003cbr\u003e - Data transformation and loading process (Transform \u0026amp; Load) ......\u003cbr\u003e 361\u003cbr\u003e - DuckDB and Milvus loading dualization ....................\u003cbr\u003e 393\u003cbr\u003e - Streamlit Image Search Example ......................\u003cbr\u003e 400\u003cbr\u003e - Building a web app using FastAPI and Streamlit ............\u003cbr\u003e 403 \u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e GOODS SPECIFICS \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eDate of issue:\u003c\/strong\u003e September 2, 2025\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003ePage count, weight, size:\u003c\/strong\u003e 408 pages | 148*210mm\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN13:\u003c\/strong\u003e 9791112052599 \u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cspan\u003e\u003c\/span\u003e\n\n\u003c\/center\u003e\n\n\n\u003c\/center\u003e","brand":"LIBRAIRIE COREENNE","offers":[{"title":"Default Title","offer_id":43893380939818,"sku":"139849","price":49.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/2949bae870227063940b953fe0b0efd1.jpg?v=1765399342","url":"https:\/\/librairie.coreenne.fr\/en\/products\/139849","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}