{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"智能化的數據管理與分析可以幫助企業打造數據資產，實現數字化轉型。Kyligence 基於人工智能和機器學習，爲用戶提供自動化的數據服務與管理，我們將在 infoQ 寫作平臺分享相關的前沿技術、趨勢以及案例，期待您的關注。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"【前沿技術分享】","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"1. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/2f12fad236586d5d1e6958884","title":"","type":null},"content":[{"type":"text","text":"深度解讀｜Spark 中 CodeGen 與向量化技術的研究","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"由 Kyligence 主辦的首期 Data & AI Meetup 中，暢銷書《深入理解 Spark 》作者、Kyligence 高級性能工程師耿嘉安帶來了主題爲「","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"Spark Code Generation & Vectorization","attrs":{}},{"type":"text","text":"」的分享，深入淺出地講解了「Spark 爲什麼需要 CodeGen」、「Spark CodeGen 與向量化原理」、「Spark 向量化的前沿」等多個與 Spark 有關的熱門話題。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"2. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/0587e0e0f9393c01b70504b74","title":"","type":null},"content":[{"type":"text","text":"MLSQL：融合 Spark+Ray，讓企業低成本落地 Data+AI","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"由 Kyligence 主辦的 Data & Cloud Summit 2021 行業峯會特設「開源有道」分論壇，來自 Apache Kylin，Apache Spark，Alluxio，Linkis，Ray 以及 MLSQL 等開源社區的技術大佬分享了目前開源社區關於大數據、機器學習等多個熱門話題的前沿技術和最佳實踐。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"3. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/931c0855a575caaeb9ce57d13","title":"","type":null},"content":[{"type":"text","text":"列存數據庫，不只是列式存儲 ","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"本文將從大數據存儲格式的變遷；存取方式中 Early Materialization 和 Late Materialization 的權衡取捨；執行框架向優化 CPU 的方向邁進；關係算子結合存儲進行優化等幾個方面出發，對列存數據庫進行詳細講解。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"4. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/3ced712e1b5fccc9d22a42d54","title":"","type":null},"content":[{"type":"text","text":"複雜分析場景，SQL or MDX ？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"提起 SQL，相信從事過數據分析相關工作的同學，對此都不陌生。在零售、銀行、物流等行業，業務往往會有複雜的分析需求，如半累加，多對多，時間窗口分析等，SQL 在處理這些場景時，就有些捉襟見肘了。那有什麼方案能夠輕鬆應對呢 ? 答案就是： MDX。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"5. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/d3efc9f6254810efb5b77d071","title":"","type":null},"content":[{"type":"text","text":"不用 Python/R ，只會 SQL 就可以做機器學習？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"要想搞定機器學習，好像非學 Python 或 R 語言不可，想只用 SQL 就能搞定機器學習？當然可以！MLSQL —— 站在 SQL 的肩膀上看大數據 + AI。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"6. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/10f45f6b628a5edca63aa51db","title":"","type":null},"content":[{"type":"text","text":"淺談OLAP系統核心技術點","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"OLAP 系統廣泛應用於 BI, Reporting, Ad-hoc, ETL 數倉分析等場景，本文主要從體系化的角度來分析 OLAP 系統的核心技術點，從業界已有的 OLAP 中萃取其共性，分爲談存儲，談計算，談優化器，談趨勢 4 個部分展開討論。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"7. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/2bfe09900c64e89d6c39198e6","title":"","type":null},"content":[{"type":"text","text":"大數據+雲：Kylin/Spark/Clickhouse/Hudi 的大佬們怎麼看？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Kylin 五週年慶典上，來自 Spark，Hudi，Clickhouse 以及 Kylin 等開源社區的大佬，來了一場跨越時差，跨越區域的“雲”上對談。下一代雲上數據分析產品的趨勢都有哪些？他們都看好什麼關鍵性技術呢？你想知道的都在本文啦！","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"【前沿趨勢分享】","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"8. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/4aa46bf44061ee574d1757480","title":"","type":null},"content":[{"type":"text","text":"Gartner 報告最新解讀：數倉 or 數據湖？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Gartner 近期發佈了一份“分析查詢加速的市場引導報告（Market Guide for Analytics Query Accelerators）”，報告中提到一個新的數據分析細分市場正在興起，即數倉和數據湖這個模糊地帶，小編特別邀請了本司產品總監帶大家一同解讀這篇專業報告。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"9. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/9e7195a1a5251f20780626521","title":"","type":null},"content":[{"type":"text","text":"後 Hadoop 時代的大數據分析路在何方？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Apache Hadoop 作爲一個完整的開源大數據套件，在過去的十多年裏深刻影響了整個計算機界，隨着各類新興技術的發展， Hadoop 生態圈也發生了巨大的變化，Kyligence 合夥人兼首席架構師史少鋒先生將從 Hadoop 的發展歷程、大數據分析的未來展望等角度展開討論。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"10. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/84f1f18dc775f9ef35609d1df","title":"","type":null},"content":[{"type":"text","text":"爲什麼預計算技術代表大數據行業的未來，一文讀懂","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"瞭解 Kylin 的技術同仁，一定對預計算這個概念不陌生。業內對於預計算的價值一直褒貶不一，本文將結合作者自身十多年的工作經驗，從預計算的歷史、原理到企業的應用，以及未來的發展來爲大家帶來更爲全面的解讀爲什麼預計算技術代表大數據行業的未來。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"11. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/2c6f5f49305a8851cbbc6fb7a","title":"","type":null},"content":[{"type":"text","text":"預計算 or 數據虛擬化，你pick誰？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"預計算側重於生產環境中的性能、響應時間和併發性；數據虛擬化技術則側重於通過減少或消除 ETL（抽取、轉換和加載）過程，從而方便用戶進行分析，兩種技術都在努力應對類似的挑戰：在現代大數據環境中，讓更廣泛的受衆輕鬆訪問分析，如何選擇，本文幫你權衡。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"12. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/d8791e71004409519f8d61d0d","title":"","type":null},"content":[{"type":"text","text":"從 Hadoop 到雲原生：Kyligence 在雲原生巨浪中的思考","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"越來越多的企業客戶正在從 On-Premise 的數倉方案，轉向基於雲（包含公有云和私有云）的解決方案，這種趨勢在美國 2B 市場已經被廣泛接受，在國內 2B 市場也已方興未艾。通過本文，可以看到數據倉庫的發展方式，即正在向雲原生的、存儲計算分離的方向上發展。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"13. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/7dd367d640a82a74de69f90a9","title":"","type":null},"content":[{"type":"text","text":"雲原生時代，企業如何智能管理數據？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"雲原生時代，數據行業的假設已經有了根本性的改變，數據從集中走向天然分佈，儘管訪問數據變得比以往任何時候都容易，但分散在各處的數據給企業使用數據和管理數據帶來了更多新的挑戰。智能管理數據，將數據變成更有價值、更容易連接和分析的數據資產。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"14. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/5aa7748a27a582041cf4f97a2","title":"","type":null},"content":[{"type":"text","text":"如何快速搭建統一數據服務，讓數據資源成爲數據資產","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在數字化轉型時代，各行各業的日常工作都與數據息息相關，企業 IT 團隊都在不斷優化平臺技術，爲業務用戶提供更加高效、便捷的數據使用體驗。筆者和社區用戶交流時，見到一類“數據微服務”的設計，和我們的設計思路非常一致，希望藉此文章和各位讀者交流。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"15. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/dce85209a2a03378850538d06","title":"","type":null},"content":[{"type":"text","text":"BI + AI：洞見數據和分析的未來","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"近年來，Kyligence 在研究了數據領域的投資者、研究機構、從業者以及客戶的觀點後，看到了 5 個如從數據中心或雲到分佈式雲、分析與 AI/ML 的大融合等的正在改變數據和分析市場的宏觀趨勢。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"16. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/a2c8d75b568cbb07cac034494","title":"","type":null},"content":[{"type":"text","text":"通往數據分析平民化的成功之路","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在以數字和數據爲中心的經濟中，藉助分析洞察數據並據此明智決策，將推動從數據到業務資產的轉化。如果平民數據分析師能從數據和分析中獲取洞察，將極大縮短週期時間、節省成本並提升公司的服務能力，Kyligence 的自助分析平臺，助力平民數據分析師賦能未來。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"17. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/a72da2223e7f0e548018b0ea2","title":"","type":null},"content":[{"type":"text","text":"如何搭建批流一體大數據分析架構？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"基於 Lambda 架構升級改造後的 Kyligence 批流一體分析融合架構，不僅解決批流一體中關鍵部分的支持，同時結合 Kyligence 的其它優勢，整套方案可更便捷地在企業落地。例如圖形界面化的友好操作、支持 Hive 和 Kafka 兩種數據源、無縫集成主流的 BI 平臺等。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"zerowidth","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"【前沿實踐分享】","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"18. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/0ec64268e543ecebae0a97971","title":"","type":null},"content":[{"type":"text","text":"Kyligence + 亞馬遜雲科技丨實現雲上的精細化運營和數字化指揮","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Kyligence 聯合創始人兼 CTO 李揚出席“亞馬遜雲科技 INNOVATE｜ 數據驅動創新大會”，並發表 《 Kyligence + 亞馬遜雲科技｜實現雲上的精細化運營和數字化指揮》主題演講，結合實際應用案例給出了 Kyligence 對於企業數字化轉型過程中所面臨的困境的解答。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"19. ","attrs":{}},{"type":"link","attrs":{"href":"https://mp.weixin.qq.com/s/f2sV-fLgHolLZDoXXDV2ZQ","title":"","type":null},"content":[{"type":"text","text":"指標平臺哪家強？看 Kyligence 助力平安銀行打造統一指標平臺","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數字銀行的突破，離不開前沿科技的驅動。平安銀行依託人工智能、大數據、雲計算等領域的核心技術，不斷將新技術深度植入到經營決策和金融服務全流程，實現數字化、智能化業務運營和經營管理。對於平安銀行來說，數據賦能業務的關鍵在於降低用戶使用數據的門檻。那麼如何讓用戶使用數據變得簡單？讓我們一起來看看 Kyligence 如何助力平安銀行打造一站式數據服務平臺——潘多拉指標平臺的吧。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}
Kyligence 智能數據服務與管理相關研究
{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"智能化的數據管理與分析可以幫助企業打造數據資產，實現數字化轉型。Kyligence 基於人工智能和機器學習，爲用戶提供自動化的數據服務與管理，我們將在 infoQ 寫作平臺分享相關的前沿技術、趨勢以及案例，期待您的關注。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"【前沿技術分享】","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"1. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/2f12fad236586d5d1e6958884","title":"","type":null},"content":[{"type":"text","text":"深度解讀｜Spark 中 CodeGen 與向量化技術的研究","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"由 Kyligence 主辦的首期 Data & AI Meetup 中，暢銷書《深入理解 Spark 》作者、Kyligence 高級性能工程師耿嘉安帶來了主題爲「","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"Spark Code Generation & Vectorization","attrs":{}},{"type":"text","text":"」的分享，深入淺出地講解了「Spark 爲什麼需要 CodeGen」、「Spark CodeGen 與向量化原理」、「Spark 向量化的前沿」等多個與 Spark 有關的熱門話題。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"2. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/0587e0e0f9393c01b70504b74","title":"","type":null},"content":[{"type":"text","text":"MLSQL：融合 Spark+Ray，讓企業低成本落地 Data+AI","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"由 Kyligence 主辦的 Data & Cloud Summit 2021 行業峯會特設「開源有道」分論壇，來自 Apache Kylin，Apache Spark，Alluxio，Linkis，Ray 以及 MLSQL 等開源社區的技術大佬分享了目前開源社區關於大數據、機器學習等多個熱門話題的前沿技術和最佳實踐。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"3. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/931c0855a575caaeb9ce57d13","title":"","type":null},"content":[{"type":"text","text":"列存數據庫，不只是列式存儲 ","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"本文將從大數據存儲格式的變遷；存取方式中 Early Materialization 和 Late Materialization 的權衡取捨；執行框架向優化 CPU 的方向邁進；關係算子結合存儲進行優化等幾個方面出發，對列存數據庫進行詳細講解。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"4. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/3ced712e1b5fccc9d22a42d54","title":"","type":null},"content":[{"type":"text","text":"複雜分析場景，SQL or MDX ？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"提起 SQL，相信從事過數據分析相關工作的同學，對此都不陌生。在零售、銀行、物流等行業，業務往往會有複雜的分析需求，如半累加，多對多，時間窗口分析等，SQL 在處理這些場景時，就有些捉襟見肘了。那有什麼方案能夠輕鬆應對呢 ? 答案就是： MDX。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"5. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/d3efc9f6254810efb5b77d071","title":"","type":null},"content":[{"type":"text","text":"不用 Python/R ，只會 SQL 就可以做機器學習？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"要想搞定機器學習，好像非學 Python 或 R 語言不可，想只用 SQL 就能搞定機器學習？當然可以！MLSQL —— 站在 SQL 的肩膀上看大數據 + AI。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"6. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/10f45f6b628a5edca63aa51db","title":"","type":null},"content":[{"type":"text","text":"淺談OLAP系統核心技術點","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"OLAP 系統廣泛應用於 BI, Reporting, Ad-hoc, ETL 數倉分析等場景，本文主要從體系化的角度來分析 OLAP 系統的核心技術點，從業界已有的 OLAP 中萃取其共性，分爲談存儲，談計算，談優化器，談趨勢 4 個部分展開討論。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"7. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/2bfe09900c64e89d6c39198e6","title":"","type":null},"content":[{"type":"text","text":"大數據+雲：Kylin/Spark/Clickhouse/Hudi 的大佬們怎麼看？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Kylin 五週年慶典上，來自 Spark，Hudi，Clickhouse 以及 Kylin 等開源社區的大佬，來了一場跨越時差，跨越區域的“雲”上對談。下一代雲上數據分析產品的趨勢都有哪些？他們都看好什麼關鍵性技術呢？你想知道的都在本文啦！","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"【前沿趨勢分享】","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"8. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/4aa46bf44061ee574d1757480","title":"","type":null},"content":[{"type":"text","text":"Gartner 報告最新解讀：數倉 or 數據湖？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Gartner 近期發佈了一份“分析查詢加速的市場引導報告（Market Guide for Analytics Query Accelerators）”，報告中提到一個新的數據分析細分市場正在興起，即數倉和數據湖這個模糊地帶，小編特別邀請了本司產品總監帶大家一同解讀這篇專業報告。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"9. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/9e7195a1a5251f20780626521","title":"","type":null},"content":[{"type":"text","text":"後 Hadoop 時代的大數據分析路在何方？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Apache Hadoop 作爲一個完整的開源大數據套件，在過去的十多年裏深刻影響了整個計算機界，隨着各類新興技術的發展， Hadoop 生態圈也發生了巨大的變化，Kyligence 合夥人兼首席架構師史少鋒先生將從 Hadoop 的發展歷程、大數據分析的未來展望等角度展開討論。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"10. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/84f1f18dc775f9ef35609d1df","title":"","type":null},"content":[{"type":"text","text":"爲什麼預計算技術代表大數據行業的未來，一文讀懂","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"瞭解 Kylin 的技術同仁，一定對預計算這個概念不陌生。業內對於預計算的價值一直褒貶不一，本文將結合作者自身十多年的工作經驗，從預計算的歷史、原理到企業的應用，以及未來的發展來爲大家帶來更爲全面的解讀爲什麼預計算技術代表大數據行業的未來。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"11. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/2c6f5f49305a8851cbbc6fb7a","title":"","type":null},"content":[{"type":"text","text":"預計算 or 數據虛擬化，你pick誰？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"預計算側重於生產環境中的性能、響應時間和併發性；數據虛擬化技術則側重於通過減少或消除 ETL（抽取、轉換和加載）過程，從而方便用戶進行分析，兩種技術都在努力應對類似的挑戰：在現代大數據環境中，讓更廣泛的受衆輕鬆訪問分析，如何選擇，本文幫你權衡。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"12. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/d8791e71004409519f8d61d0d","title":"","type":null},"content":[{"type":"text","text":"從 Hadoop 到雲原生：Kyligence 在雲原生巨浪中的思考","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"越來越多的企業客戶正在從 On-Premise 的數倉方案，轉向基於雲（包含公有云和私有云）的解決方案，這種趨勢在美國 2B 市場已經被廣泛接受，在國內 2B 市場也已方興未艾。通過本文，可以看到數據倉庫的發展方式，即正在向雲原生的、存儲計算分離的方向上發展。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"13. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/7dd367d640a82a74de69f90a9","title":"","type":null},"content":[{"type":"text","text":"雲原生時代，企業如何智能管理數據？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"雲原生時代，數據行業的假設已經有了根本性的改變，數據從集中走向天然分佈，儘管訪問數據變得比以往任何時候都容易，但分散在各處的數據給企業使用數據和管理數據帶來了更多新的挑戰。智能管理數據，將數據變成更有價值、更容易連接和分析的數據資產。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"14. 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","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/dce85209a2a03378850538d06","title":"","type":null},"content":[{"type":"text","text":"BI + AI：洞見數據和分析的未來","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"近年來，Kyligence 在研究了數據領域的投資者、研究機構、從業者以及客戶的觀點後，看到了 5 個如從數據中心或雲到分佈式雲、分析與 AI/ML 的大融合等的正在改變數據和分析市場的宏觀趨勢。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"16. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/a2c8d75b568cbb07cac034494","title":"","type":null},"content":[{"type":"text","text":"通往數據分析平民化的成功之路","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在以數字和數據爲中心的經濟中，藉助分析洞察數據並據此明智決策，將推動從數據到業務資產的轉化。如果平民數據分析師能從數據和分析中獲取洞察，將極大縮短週期時間、節省成本並提升公司的服務能力，Kyligence 的自助分析平臺，助力平民數據分析師賦能未來。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"17. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/a72da2223e7f0e548018b0ea2","title":"","type":null},"content":[{"type":"text","text":"如何搭建批流一體大數據分析架構？","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"基於 Lambda 架構升級改造後的 Kyligence 批流一體分析融合架構，不僅解決批流一體中關鍵部分的支持，同時結合 Kyligence 的其它優勢，整套方案可更便捷地在企業落地。例如圖形界面化的友好操作、支持 Hive 和 Kafka 兩種數據源、無縫集成主流的 BI 平臺等。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"zerowidth","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"【前沿實踐分享】","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"18. ","attrs":{}},{"type":"link","attrs":{"href":"https://xie.infoq.cn/article/0ec64268e543ecebae0a97971","title":"","type":null},"content":[{"type":"text","text":"Kyligence + 亞馬遜雲科技丨實現雲上的精細化運營和數字化指揮","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Kyligence 聯合創始人兼 CTO 李揚出席“亞馬遜雲科技 INNOVATE｜ 數據驅動創新大會”，並發表 《 Kyligence + 亞馬遜雲科技｜實現雲上的精細化運營和數字化指揮》主題演講，結合實際應用案例給出了 Kyligence 對於企業數字化轉型過程中所面臨的困境的解答。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":4},"content":[{"type":"text","text":"19. ","attrs":{}},{"type":"link","attrs":{"href":"https://mp.weixin.qq.com/s/f2sV-fLgHolLZDoXXDV2ZQ","title":"","type":null},"content":[{"type":"text","text":"指標平臺哪家強？看 Kyligence 助力平安銀行打造統一指標平臺","attrs":{}}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數字銀行的突破，離不開前沿科技的驅動。平安銀行依託人工智能、大數據、雲計算等領域的核心技術，不斷將新技術深度植入到經營決策和金融服務全流程，實現數字化、智能化業務運營和經營管理。對於平安銀行來說，數據賦能業務的關鍵在於降低用戶使用數據的門檻。那麼如何讓用戶使用數據變得簡單？讓我們一起來看看 Kyligence 如何助力平安銀行打造一站式數據服務平臺——潘多拉指標平臺的吧。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}
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