[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"blogCategories:ja":3,"blog::vision:ja":28},[4,7,10,13,16,19,22,25],{"title":5,"slug":6},"Event Report","eventreport",{"title":8,"slug":9},"Product Guide","product-guide",{"title":11,"slug":12},"Tips & Case Study","tips-case-study",{"title":14,"slug":15},"Vision","vision",{"title":17,"slug":18},"エンジニアリング","engineering",{"title":20,"slug":21},"プロダクト","product",{"title":23,"slug":24},"プロダクト比較","product-comparison",{"title":26,"slug":27},"マーケットインサイト","market-insights",[29,41,52,62],{"title":30,"slug":31,"description":32,"author":33,"category":34,"urlCategorySlug":21,"coverImageUrl":36,"ogImageUrl":36,"createdAt":37,"updatedAt":38,"datePublished":39,"locale":40},"AIが育つデータ活用の好循環——Codatumが支える5つのステップ","ai-data-utilization-cycle","AIをデータ基盤につないでも、それだけでは正確な分析はできません。組織のデータ活用を定着させるには「好循環」を回し続ける必要があります。本記事では、AIが育つデータ活用の好循環の各ステップで起きがちな課題と解決策、そしてCodatumがどう解いているかを詳しく解説します。","Tomoya Koike",{"title":14,"slug":15,"description":35},"プロダクトの存在理由・思想を語る記事","https:\u002F\u002Fimages.ctfassets.net\u002Fggtw2zqmifs5\u002F2etynFVBIXjTuXP0DbqJKG\u002Fc9a193b0cddf184d9e3d977b3310d9e9\u002FSTEP_1.png","2026-04-01T03:47:14.561Z","2026-05-07T15:35:33.815Z","2026-04-01T12:00+09:00","ja",{"title":42,"slug":43,"description":44,"author":45,"category":46,"urlCategorySlug":21,"coverImageUrl":47,"ogImageUrl":48,"createdAt":49,"updatedAt":50,"datePublished":51,"locale":40},"なぜData Workspace x AIが、データ分析の未来を変えるのか","data-workspace-x-ai","「データ分析×AI」の新しい形：Data Workspaceが切り拓く、人とAIのコラボレーションの未来","Naoki Shibayama",{"title":14,"slug":15,"description":35},"https:\u002F\u002Fimages.ctfassets.net\u002Fggtw2zqmifs5\u002F6wAbMDuP9MsBu3gqkcOgSN\u002Fdd52c33a5fc2ca8eacfd296380db2941\u002Fdataworkspace.png","https:\u002F\u002Fimages.ctfassets.net\u002Fggtw2zqmifs5\u002F14OazFgY4nKdUOamr2WClc\u002F462c9c8e7924330ca82d08c3b63d3764\u002Fdataworkspace_og.png","2024-11-08T01:00:02.282Z","2026-05-07T15:52:40.323Z","2024-11-08T10:00+09:00",{"title":53,"slug":54,"description":55,"author":45,"category":56,"urlCategorySlug":21,"coverImageUrl":57,"ogImageUrl":58,"createdAt":59,"updatedAt":60,"datePublished":61,"locale":40},"データ分析におけるTry&Errorの重要性とそのUI","data-analysis-trial-and-error-ui","Codatumが目指す、データ分析における「試行錯誤」をサポートするプロダクトのコンセプトを解説。従来のツールの課題を指摘し、「手に馴染む」データ分析体験の重要性を強調。独自開発のBlock Editorを通じて、思考とデータ探索の融合を実現する新しいアプローチを紹介します。",{"title":14,"slug":15,"description":35},"https:\u002F\u002Fimages.ctfassets.net\u002Fggtw2zqmifs5\u002F6LHt1dtZ65IML3fCwsycpU\u002Fba67ff3a6604c6adfd932d341d9ece9b\u002Fcover.jpg","https:\u002F\u002Fimages.ctfassets.net\u002Fggtw2zqmifs5\u002F3JN1UpE1zvBmTfariMFiXW\u002F99245f50b891bc3e489b489e4aa7f14f\u002Fog.jpg","2024-10-07T07:02:59.715Z","2026-05-07T15:35:30.430Z","2024-10-07T16:00+09:00",{"title":63,"slug":64,"description":65,"author":45,"category":66,"urlCategorySlug":21,"coverImageUrl":67,"ogImageUrl":68,"createdAt":69,"updatedAt":70,"datePublished":71,"locale":40},"なぜ「Codatum」を作っているのか: SQLファーストなデータ分析ツール","why-we-are-creating-codatum-sql-first-data-analysis-tool","私たちの会社は、CodatumというSQLファーストなデータ分析ツールを開発しています。Codatumはエンジニアを含むあらゆる人がデータ分析に積極的に参加できる環境を提供することを目指しています、今回の記事ではこのCodatumの開発を始めた背景をお話しします。",{"title":14,"slug":15,"description":35},"https:\u002F\u002Fimages.ctfassets.net\u002Fggtw2zqmifs5\u002FCWUu8BTQ1FpltNJvxrSdO\u002F4d7429848791cd6097593f5d2fe40798\u002Fcover.jpg","https:\u002F\u002Fimages.ctfassets.net\u002Fggtw2zqmifs5\u002F6jT2fzeae7eYLPu3h68TZ1\u002Fdc4c7fab16e14fad6bc975a02dc90afa\u002Fcover.jpg","2024-10-01T04:55:48.657Z","2026-05-07T15:35:26.564Z","2024-09-26T13:00+09:00"]