數據湖 VS 數據倉庫，哪個更好用？

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"任何數據都需要保護、存儲和管理，以便更好地應用。本文對比了數據倉庫和數據湖這兩個大數據存儲和處理中的不同概念，分別從定義、特點和應用方面比較了它們之間的差異，方便你在業務中作出正確的選擇。"}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"目前，數據仍然是技術創新的關鍵之一，任何數據都需要保護、存儲和管理以便更好地應用。毋庸置疑，有效和合理的數據利用確實可以爲各類企業帶來不一樣的收益。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"本文涉及大數據存儲和處理的兩個不同概念：數據倉庫和數據湖。你將認識到它們的主要優點，併爲業務作出正確的選擇。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"數據倉庫：定義、特點和應用"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據倉庫是一個用於實現和支持各種業務活動的系統，關係到大數據分析和結構化。通常情況下，"},{"type":"link","attrs":{"href":"https:\/\/www.forbes.com\/sites\/forbestechcouncil\/2020\/07\/07\/data-lakes-and-data-warehouses-the-two-sides-of-a-modern-cloud-data-platform\/?sh=457a6681f1b1","title":"","type":null},"content":[{"type":"text","text":"數據倉庫系統"}]},{"type":"text","text":"產出的報告被用於目標分析、業務戰略發展和工作彙報。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"由於採用實時數據分析，該系統可以提供最新的信息，進而很容易應用在業務的各個方面。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據倉庫系統的基本功能包括"},{"type":"text","marks":[{"type":"strong"}],"text":"報告、可視化和商業智能"},{"type":"text","text":"，這使它成爲完美的業務分析工具。此外，以下特點也促成了它的廣泛應用："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"靈活性，無論數據的原始來源是什麼，它總能用相同的算法進行提取和轉換。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"可靠性，數據倉庫通常在預定時間更新，這大大減少了實時變化的影響。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"可擴展性，能利用任何大小的數據，並適用於任何存儲空間。"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據倉庫適用於結構化和已處理的數據類型，並提供數據聚合和彙總的只讀查詢，寫入機制和預處理功能使其成爲商業分析"},{"type":"link","attrs":{"href":"https:\/\/www.scnsoft.com\/analytics\/data-warehouse\/implementation","title":"","type":null},"content":[{"type":"text","text":"實施"}]},{"type":"text","text":"的完美選擇。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據倉庫一般應用於銀行、金融、公共部門或酒店業，數據存儲之前通常要進行預處理。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https:\/\/static001.geekbang.org\/resource\/image\/ec\/0a\/ec24afd5ccd6849yye3189d6a104230a.png","alt":null,"title":null,"style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":null,"fromPaste":true,"pastePass":true}},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"數據湖：定義、特點和應用"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據湖系統以原始格式存儲數據，可以存儲結構化（表格或圖形）、半結構化（CSV、JSON、日誌）、非結構化（電子郵件、文檔）和二進制數據（音頻、照片等）。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據湖與其他數據系統主要區別如下："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"易用，數據湖可以存儲不同來源、不同類型的數據，方便進一步分析和重新安置"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"組織和結構化，數據是以原始格式進行實時收集和存儲"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"實惠，能爲任何規模的數據提供划算的價格"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"適用於任何時間框架，可以實時或按需更新"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"無限存儲空間，爲大數據存儲提供優秀的解決方案。"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"不同於數據倉庫，數據湖可以完美地處理不同類型的數據，而且因爲能提供高性價比的大數據存儲而備受讚賞。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"它的這些功能主要提供給數據科學家和工程師，他們需要足夠的空間來存儲所有的重要數據和項目細節，並在深度學習、實時分析及其他方面採用該系統。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https:\/\/static001.geekbang.org\/resource\/image\/e3\/f9\/e3d62ea03458cf4eaf81217dbe155ef9.png","alt":null,"title":null,"style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":null,"fromPaste":true,"pastePass":true}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":"center","origin":null},"content":[{"type":"text","text":"圖片來自"},{"type":"link","attrs":{"href":"https:\/\/www.n-ix.com\/data-lake-vs-data-warehouse\/","title":"","type":null},"content":[{"type":"text","text":"https:\/\/www.n-ix.com"}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據湖通常應用於醫療、教育、交通這些行業，它既可以提供實時洞察，還能提供一個檢測和預防各種潛在問題的未來預測清單。這些領域通常都需要數據後處理程序，而此類程序可以通過數據湖系統輕鬆實現。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"哪個更好用？"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"總而言之，是用數據湖還是數據倉庫，完全取決於你的需求、目標和期望。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"有了數據倉庫系統，你可以利用經過組織和預分類的數據達成更進一步的目的，而數據湖系統則可以按原始大小和格式爲你存儲數據。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在瞭解每種系統的主要特點以及傳統上用於哪些行業之後，你應該會更容易確定哪個系統最適合你的業務。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"作者介紹："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Conrad Sturdy，自由撰稿人，熱愛戶外活動，相信新鮮空氣會帶來新的靈感。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"原文鏈接："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"link","attrs":{"href":"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/data-lake-vs-data-warehouse-what-is-the-difference","title":"","type":null},"content":[{"type":"text","text":"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/data-lake-vs-data-warehouse-what-is-the-difference"}]}]}]}