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[20+ 新闻通讯推荐](newsletters.md)","术语表："],"readme":"# 数据工程手册\n\n这个仓库包含了成为一名优秀数据工程师所需的所有资源！\n\n## 入门指南\n\n如果你刚刚接触数据工程，可以先查看这份[2024年数据工程入门路线图](https://blog.dataengineer.io/p/the-2024-breaking-into-data-engineering)。\n\n如果你是为了参加[6周免费YouTube训练营](https://youtu.be/myhe0LXpCeo)而来的，可以先查看以下内容：\n- [简介](bootcamp/introduction.md)\n- [所需软件](bootcamp/software.md)\n\n更多实战学习内容：\n- 参考[项目](projects.md)部分，获取更多实操示例！\n- 参考[面试](interviews.md)部分，获取通过数据工程面试的建议！\n- 参考[书籍](books.md)部分，了解优质的数据工程书籍推荐。\n- 参考[社区](communities.md)部分，加入高质量的数据工程社区。\n- 参考[新闻通讯](newsletters.md)部分，通过电子邮件获取学习资源。\n\n---\n以下是经过调整，更适合中国人理解的版本：\n\n---\n\n### 精选的[超过25本数据工程经典书籍列表](books.md)\n\n推荐必读的三本书：\n- [数据工程基础](https://www.amazon.com/Fundamentals-Data-Engineering-Robust-Systems/dp/1098108302/)\n- [设计数据密集型应用](https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321/)\n- [设计机器学习系统](https://www.amazon.com/Designing-Machine-Learning-Systems-Production-Ready/dp/1098107969)\n\n### 精选的[超过10个值得加入的数据工程社区](communities.md)\n\n推荐加入的数据工程社区：\n- [EcZachly 数据工程 Discord](https://discord.gg/JGumAXncAK)\n- [Data Talks Club Slack](https://datatalks.club/slack)\n- [Data Engineer Things 社区](https://www.dataengineerthings.org/aboutus/)\n\n推荐加入的机器学习社区：\n- [AdalFlow Discord](https://discord.com/invite/ezzszrRZvT)\n- [Chip Huyen MLOps Discord](https://discord.gg/dzh728c5t3)\n\n### 数据工程公司分类\n\n- 编排工具 \n - [Mage](https://www.mage.ai)\n - [Astronomer](https://www.astronomer.io)\n - [Prefect](https://www.prefect.io)\n - [Dagster](https://www.dagster.io)\n - [Airflow](https://airflow.apache.org/)\n - [Kestra](https://kestra.io/)\n - [Shipyard](https://www.shipyardapp.com/)\n - [Hamilton](https://github.com/dagworks-inc/hamilton)\n- 数据湖 / 云平台\n - [Tabular](https://www.tabular.io)\n - [Microsoft](https://www.microsoft.com)\n - [Databricks](https://www.databricks.com/company/about-us)\n - [Onehouse](https://www.onehouse.ai)\n - [Delta Lake](https://delta.io/)\n- 数据仓库\n - [Snowflake](https://www.snowflake.com/en/)\n - [Firebolt](https://www.firebolt.io/)\n- 数据质量\n - [dbt](https://www.getdbt.com/)\n - [Gable](https://www.gable.ai)\n - [Great Expectations](https://www.greatexpectations.io)\n - [Streamdal](https://streamdal.com)\n - [Coalesce](https://coalesce.io/)\n - [Soda](https://www.soda.io/)\n - [DQOps](https://dqops.com/)\n - [HEDDA.IO](https://hedda.io)\n- 教育平台\n - [DataExpert.io](https://www.dataexpert.io)\n - [LearnDataEngineering.com](https://www.learndataengineering.com)\n - [AlgoExpert](https://www.algoexpert.io)\n - [ByteByteGo](https://www.bytebytego.com)\n- 分析 / 可视化工具\n - [Preset](https://www.preset.io)\n - [Starburst](https://www.starburst.io)\n - [Metabase](https://www.metabase.com/)\n - [Looker Studio](https://lookerstudio.google.com/overview)\n - [Tableau](https://www.tableau.com/)\n - [Power BI](https://powerbi.microsoft.com/)\n - [Apache Superset](https://superset.apache.org/)\n - [Evidence](https://evidence.dev)\n- 数据集成工具\n - [Cube](https://cube.dev)\n - [Fivetran](https://www.fivetran.com)\n - [Airbyte](https://airbyte.io)\n - [dlt](https://dlthub.com/)\n - [Sling](https://slingdata.io/)\n - [Meltano](https://meltano.com/)\n- 现代OLAP工具\n - [Apache Druid](https://druid.apache.org/)\n - [ClickHouse](https://clickhouse.com/)\n - [Apache Pinot](https://pinot.apache.org/)\n - [Apache Kylin](https://kylin.apache.org/)\n - [DuckDB](https://duckdb.org/)\n - [QuestDB](https://questdb.io/)\n- 大语言模型（LLM）应用库\n - [AdalFlow](https://github.com/SylphAI-Inc/AdalFlow)\n - [LangChain](https://github.com/langchain-ai/langchain)\n - [LlamaIndex](https://github.com/run-llama/llama_index)\n- 实时数据处理工具\n - [Aggregations.io](https://aggregations.io)\n - [Responsive](https://www.responsive.dev/)\n - [RisingWave](https://risingwave.com/)\n - [Striim](https://www.striim.com/)\n\n### 公司博客中的数据工程内容：\n\n- [Netflix](https://netflixtechblog.com/tagged/big-data)\n- [Uber](https://www.uber.com/blog/houston/data/?uclick_id=b2f43229-f3f4-4bae-bd5d-10a05db2f70c)\n- [Databricks](https://www.databricks.com/blog/category/engineering/data-engineering)\n- [Airbnb](https://medium.com/airbnb-engineering/data/home)\n- [亚马逊 AWS Blog](https://aws.amazon.com/blogs/big-data/)\n- [微软数据架构博客](https://techcommunity.microsoft.com/t5/data-architecture-blog/bg-p/DataArchitectureBlog)\n- [微软 Fabric Blog](https://blog.fabric.microsoft.com/)\n- [Oracle](https://blogs.oracle.com/datawarehousing/)\n- [Meta](https://engineering.fb.com/category/data-infrastructure/)\n- [Onehouse](https://www.onehouse.ai/blog)\n\n### 数据工程领域的白皮书：\n\n- [五层商业智能架构](https://ibimapublishing.com/articles/CIBIMA/2011/695619/695619.pdf)\n- [湖仓一体：新一代统一数据仓储与高级分析平台](https://www.cidrdb.org/cidr2021/papers/cidr2021_paper17.pdf)\n- [大数据质量：一种数据质量分析模型](https://link.springer.com/chapter/10.1007/978-3-030-23381-5_5)\n- [湖仓体系：数据仓库及其他](https://arxiv.org/abs/2310.08697)\n- [Spark：基于工作集的集群计算](https://dl.acm.org/doi/10.5555/1863103.1863113)\n- [Google 文件系统](https://research.google/pubs/the-google-file-system/)\n- [构建通用数据湖仓](https://www.onehouse.ai/whitepaper/onehouse-universal-data-lakehouse-whitepaper)\n- [XTable 实战：数据湖中的无缝互操作](https://arxiv.org/abs/2401.09621)\n- [MapReduce：简化大规模集群的数据处理](https://research.google/pubs/mapreduce-simplified-data-processing-on-large-clusters/)\n\n## 社交媒体账号列表\n\n这里是数据工程领域创作者的几乎完整列表：\n**（需要至少有5k粉丝才能加入这个列表！）**\n\n| 姓名 | \u003cimg src=\"https://upload.wikimedia.org/wikipedia/commons/4/42/YouTube_icon_%282013-2017%29.png\" width=\"50\"/\u003e\u003cbr/\u003e YouTube | \u003cimg src=\"https://upload.wikimedia.org/wikipedia/commons/c/ca/LinkedIn_logo_initials.png\" width=\"50\" height=\"50\"/\u003e \u003cbr/\u003e LinkedIn | \u003cimg src=\"https://icon2.cleanpng.com/20240402/kzp/transparent-x-logo-woman-black-and-white-photography-street-fa-woman-in-dark-clothing-walking-determinedly660c4b50383a25.14507568.webp\" width=\"50\"\u003e\u003cbr/\u003e X/Twitter | \u003cimg src=\"https://upload.wikimedia.org/wikipedia/commons/a/a5/Instagram_icon.png\" width=\"50\"\u003e \u003cbr/\u003e Instagram | \u003cimg src=\"https://icon2.cleanpng.com/20240214/kxl/transparent-tiktok-logo-tiktok-logo-blue-and-pink-lettering-re-retro-style-tiktok-logo-evoking-1950s-1710878265139.webp\" width=\"50\"\u003e \u003cbr/\u003e TikTok |\n|----------------------|---------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Zach Wilson | [Data with Zach](https://www.youtube.com/@eczachly_) (70k+) | [Zach Wilson](https://www.linkedin.com/in/eczachly) (400k+) | [EcZachly](https://www.twitter.com/EcZachly) (30k+) | [eczachly](https://www.instagram.com/eczachly) (150k+) | [@eczachly](https://www.tiktok.com/@eczachly) (70k+) |\n| Shashank Mishra | [E-learning Bridge](https://www.youtube.com/@shashank_mishra) (100k+) | [Shashank Mishra](https://www.linkedin.com/in/shashank219/) (100k+) | | | |\n| Seattle Data Guy | [Seattle Data Guy](https://www.youtube.com/c/SeattleDataGuy) (100k+) | [Ben Rogojan](https://www.linkedin.com/in/benjaminrogojan) (100k+) | [SeattleDataGuy](https://www.twitter.com/SeattleDataGuy) (10k+) | | |\n| TrendyTech | [TrendyTech](https://www.youtube.com/c/TrendytechInsights) (100k+) | [Sumit Mittal](https://www.linkedin.com/in/bigdatabysumit/) (100k+) | | | |\n| Darshil Parmar | [Darshil Parmar](https://www.youtube.com/@DarshilParmar) (100k+) | [Darshil Parmar](https://www.linkedin.com/in/darshil-parmar/) (100k+) | | | |\n| Andreas Kretz | [Andreas Kretz](https://www.youtube.com/c/andreaskayy) (100k+) | [Andreas Kretz](https://www.linkedin.com/in/andreas-kretz) (100k+) | | [learndataengineering](https://www.instagram.com/learndataengineering) (5k+) | |\n| ByteByteGo | [ByteByteGo](https://www.youtube.com/c/ByteByteGo) (1m+) | [Alex Xu](https://www.linkedin.com/in/alexxubyte) (100k+) | [alexxubyte](https://twitter.com/alexxubyte/) (100k+) | | |\n| The Ravit Show | [The Ravit Show](https://youtube.com/@theravitshow) (100k+) | | | | |\n| Guy in a Cube | [Guy in a Cube](https://www.youtube.com/@GuyInACube) (100k+) | | | | |\n| Adam Marczak | [Adam Marczak](https://www.youtube.com/@AdamMarczakYT) (100k+) | | | | |\n| nullQueries | [nullQueries](https://www.youtube.com/@nullQueries) (100k+) | | | | |\n| TECHTFQ by Thoufiq | [TECHTFQ by Thoufiq](https://www.youtube.com/@techTFQ) (100k+) | | | | |\n| SQLBI | [SQLBI](https://www.youtube.com/@SQLBI) (100k+) | [Marco Russo](https://www.linkedin.com/in/sqlbi) (50k+) | [marcorus](https://x.com/marcorus) (10k+) | | |\n| Azure Lib | [Azure Lib](https://www.youtube.com/@azurelib-academy) (10k+) | [Deepak Goyal](https://www.linkedin.com/in/deepak-goyal-93805a17/) (100k+) | | | |\n| Advancing Analytics | [Advancing Analytics](https://www.youtube.com/@AdvancingAnalytics) (10k+) | [Simon Whiteley](https://www.linkedin.com/in/simon-whiteley-uk/) (10k+) | | | |\n| Kahan Data Solutions | [Kahan Data Solutions](https://www.youtube.com/@KahanDataSolutions) (10k+) | | | | |\n| Ankit Bansal | [Ankit Bansal](https://youtube.com/@ankitbansal6) (10k+) | [Ankit Bansal](https://www.linkedin.com/in/ankitbansal6/) (50k+) | | | |\n| Mr. K Talks Tech | [Mr. K Talks Tech](https://www.youtube.com/channel/UCzdOan4AmF65PmLLks8Lmww) (10k+) | | | | |\n| Li Yin | | [Li Yin](https://www.linkedin.com/in/li-yin-ai/) (10k+) | | | |\n| Jaco van Gelder | | [Jaco van Gelder](https://www.linkedin.com/in/jwvangelder/) (10k+) | | | |\n| Joseph Machado | | [Joseph Machado](https://www.linkedin.com/in/josephmachado1991/) (10k+) | [startdataeng](https://twitter.com/startdataeng) (5k+) | | |\n| Eric Roby | | [Eric Roby](https://www.linkedin.com/in/codingwithroby/) (10k+) | | | |\n| Simon Späti | | [Simon Späti](https://www.linkedin.com/in/sspaeti/) (10k+) | | | |\n| Dipankar Mazumdar | | [Dipankar Mazumdar](https://www.linkedin.com/in/dipankar-mazumdar/) (5k+) | | | |\n| Daniel Ciocirlan | | [Daniel Ciocirlan](https://www.linkedin.com/in/danielciocirlan) (5k+) | | | |\n| Hugo Lu | | [Hugo Lu](https://www.linkedin.com/in/hugo-lu-confirmed/) (5k+) | | | |\n| Tobias Macey | | [Tobias Macey](https://www.linkedin.com/in/tmacey) (5k+) | | | |\n| Marcos Ortiz | | [Marcos Ortiz](https://www.linkedin.com/in/mlortiz) (5k+) | | | |\n| Julien Hurault | | [Julien Hurault](https://www.linkedin.com/in/julienhuraultanalytics/) (5k+) | | | |\n| Alex Freberg | [Alex The Analyst](https://www.youtube.com/@AlexTheAnalyst) (100k+) | [Alex Freberg](https://www.linkedin.com/in/alex-freberg/) (100k+) | | | [@alex_the_analyst](https://www.tiktok.com/@alex_the_analyst) (10k+) |\n| Marc Lamberti | | [Marc Lamberti](https://www.linkedin.com/in/marclamberti) (50k+) | | | |\n| Chip Huyen | | [Chip Huyen](https://www.linkedin.com/in/chiphuyen/) (250k+) | | | |\n| Alex Merced | [Alex Merced Data](https://www.youtube.com/@alexmerceddata_) | [Alex Merced](https://www.linkedin.com/in/alexmerced) (30k+) | [@amdatalakehouse](https://www.twitter.com/amdatalakehouse) | [@alexmercedcoder](https://www.instagram.com/alexmercedcoder) | | \n| John Kutay | [John Kutay](https://www.youtube.com/watch?v=7K09lxNbF3Q\u0026list=PL1EXPn7cSg91KLnk2P26Fh8OnGrh6eFmx\u0026pp=iAQB) | [John Kutay](https://www.linkedin.com/in/johnkutay/) (5k+) | [@JohnKutay](https://x.com/JohnKutay) | | |\n| Lakshmi Sontenam | | [Lakshmi Sontenam](https://www.linkedin.com/in/shivaga9esh) (9.5k+) | | | |\n| Hassaan Akbar | | [Hassaan Akbar](https://www.linkedin.com/in/ehassaan) (5k+) | | | |\n| Samuel Focht | [Python Basics ](https://www.youtube.com/@PythonBasics) (10k+) | | | | |\n| Constantin Lungu | | [Constantin Lungu](https://www.linkedin.com/in/constantin-lungu-668b8756) (10k+) | | | | \n| Ijaz Ali | | [Ijaz Ali](https://www.linkedin.com/in/ijaz-ali-6aaa87122/) (24K+) |\n| Subhankar | | [Subhankar](https://www.linkedin.com/in/subhankarumass/) (5k+) | | | |\n| Ankur Ranjan | [Big Data Show](https://www.youtube.com/@TheBigDataShow) (100k+) | [Ankur Ranjan](https://www.linkedin.com/in/thebigdatashow/) (48k+) \n\n### 优秀播客推荐\n\n- [数据工程秀](https://www.dataengineeringshow.com/)\n- [数据工程播客](https://www.dataengineeringpodcast.com/)\n- [数据话题](https://www.datatopics.io/)\n- [数据工程的另一面](https://podcasts.apple.com/us/podcast/the-engineering-side-of-data/id1566999533)\n- [数据感知](https://www.ascend.io/dataaware-podcast/)\n- [数据咖啡时刻](https://www.deezer.com/us/show/5293247)\n- [数据栈秀](https://datastackshow.com/)\n- [Intricity101 数据鲨鱼播客](https://www.intricity.com/learningcenter/podcast)\n- [深入探讨与 Mark Rittman](https://www.rittmananalytics.com/drilltodetail/)\n- [分析力量时刻](https://analyticshour.io/)\n- [目录与鸡尾酒](https://listen.casted.us/public/127/Catalog-%26-Cocktails-2fcf8728)\n- [数据对话](https://datatalks.club/podcast.html)\n- [Databricks 的数据酿造](https://www.databricks.com/discover/data-brew)\n- [Snowflake 的数据云播客](https://rise-of-the-data-cloud.simplecast.com/)\n- [数据新鲜事](https://www.striim.com/podcast/)\n- [Datastax 的开源数据](https://www.datastax.com/resources/podcast/open-source-data)\n- [Confluent 的流音频](https://developer.confluent.io/podcast/)\n- [数据科学家秀](https://podcasts.apple.com/us/podcast/the-data-scientist-show/id1584430381)\n- [MLOps 社区播客](https://podcast.mlops.community/)\n- [周一早晨数据聊天](https://open.spotify.com/show/3Km3lBNzJpc1nOTJUtbtMh)\n- [数据首席](https://www.thoughtspot.com/data-chief/podcast)\n\n### 优秀 [20+ 新闻通讯推荐](newsletters.md)\n\n数据工程领域必关注的新闻通讯：\n- [DataEngineer.io 新闻通讯](https://blog.dataengineer.io)\n- [Joe Reis 的通讯](https://joereis.substack.com)\n- [Start Data Engineering](https://www.startdataengineering.com)\n- [数据工程周刊](https://www.dataengineeringweekly.com)\n\n### 术语表：\n- [数据工程宝库](https://www.ssp.sh/brain/data-engineering/)\n- [Airbyte 数据术语表](https://glossary.airbyte.com/)\n- [Reddit 数据工程百科](https://dataengineering.wiki/Index)\n- [Seconda 术语表](https://www.secoda.co/glossary/)\n- [Databricks 术语表](https://www.databricks.com/glossary)\n- [Airtable 术语表](https://airtable.com/shrGh8BqZbkfkbrfk/tbluZ3ayLHC3CKsDb)\n- [Dagster 的数据工程术语表](https://dagster.io/glossary)\n\n### 优质播客推荐\n\n以下是一些与数据工程相关的优质播客：\n\n- [The Data Engineering Show](https://www.dataengineeringshow.com/) \n- [Data Engineering Podcast](https://www.dataengineeringpodcast.com/) \n- [DataTopics](https://www.datatopics.io/) \n- [The Data Engineering Side Of Data](https://podcasts.apple.com/us/podcast/the-engineering-side-of-data/id1566999533) \n- [DataWare](https://www.ascend.io/dataaware-podcast/) \n- [The Data Coffee Break Podcast](https://www.deezer.com/us/show/5293247) \n- [The Datastack Show](https://datastackshow.com/) \n- [Intricity101 Data Sharks Podcast](https://www.intricity.com/learningcenter/podcast) \n- [Drill to Detail with Mark Rittman](https://www.rittmananalytics.com/drilltodetail/) \n- [Analytics Power Hour](https://analyticshour.io/) \n- [Catalog \u0026 Cocktails](https://listen.casted.us/public/127/Catalog-%26-Cocktails-2fcf8728) \n- [Datatalks](https://datatalks.club/podcast.html) \n- [Data Brew by Databricks](https://www.databricks.com/discover/data-brew) \n- [The Data Cloud Podcast by Snowflake](https://rise-of-the-data-cloud.simplecast.com/) \n- [What's New in Data](https://www.striim.com/podcast/) \n- [Open||Source||Data by Datastax](https://www.datastax.com/resources/podcast/open-source-data) \n- [Streaming Audio by Confluent](https://developer.confluent.io/podcast/) \n- [The Data Scientist Show](https://podcasts.apple.com/us/podcast/the-data-scientist-show/id1584430381) \n- [MLOps.community](https://podcast.mlops.community/) \n- [Monday Morning Data Chat](https://open.spotify.com/show/3Km3lBNzJpc1nOTJUtbtMh) \n- [The Data Chief](https://www.thoughtspot.com/data-chief/podcast) \n\n---\n\n### 优质数据工程资讯订阅\n\n以下是一些值得关注的数据工程相关电子报：\n\n- [DataEngineer.io Newsletter](https://blog.dataengineer.io) \n- [Joe Reis 的专栏](https://joereis.substack.com) \n- [Start Data Engineering](https://www.startdataengineering.com) \n- [Data Engineering Weekly](https://www.dataengineeringweekly.com) \n\n---\n\n### 数据工程术语资源\n\n以下是一些数据工程术语的学习资源：\n\n- [Data Engineering Vault](https://www.ssp.sh/brain/data-engineering/) \n- [Airbyte 数据术语库](https://glossary.airbyte.com/) \n- [Reddit 的数据工程 Wiki](https://dataengineering.wiki/Index) \n- [Seconda 术语库](https://www.secoda.co/glossary/) \n- [Databricks 术语库](https://www.databricks.com/glossary) \n- [Airtable 术语库](https://airtable.com/shrGh8BqZbkfkbrfk/tbluZ3ayLHC3CKsDb) \n- [Dagster 的数据工程术语库](https://dagster.io/glossary) \n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/xiaomingx%2Fawesome-data-engineer/projects"}