Modernising Data Architecture for Data Driven Insights (Chinese)Denodo
Watch full webinar here: https://bit.ly/3phVEEv
In an era increasingly dominated by advancements in cloud computing, AI and advanced analytics, it may come as a shock that many organizations still rely on data architectures built before the turn of the century. But, that scenario is rapidly changing with the increasing adoption of real-time data virtualization - A paradigm shift in the approach that organisations take towards accessing, integrating, and provisioning data required to meet business goals.
As data analytics and data-driven intelligence takes center stage in today’s digital economy, logical data integration across the widest variety of data sources, with proper security and governance structure in place has become mission critical.
Register this webinar to learn:
- How you can meet the challenges of delivering data insights with data virtualization
- Why Data Virtualization is increasingly find enterprise-wide adoption
- How customers are reducing costs and delivering faster insight
Advanced Analytics and Machine Learning with Data Virtualization (Chinese)Denodo
Watch full webinar here: https://bit.ly/3mLNJ1J
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Attend this webinar and learn:
- How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo
- How you can use the Denodo Platform with large data volumes in an efficient way
- How Prologis accelerated their use of Machine Learning with data virtualization
海量計算的學習歷程分析與雲端資料庫管理系統Sqlmr appliance一體機開發計畫書 20140101Jackie Liu
硬體形式的一體機(Appliance)
End-to-End Big Data Solution in a Box
因應巨量資料處理需求,使用者大致上有幾個不同部署型態選擇,除了採用套裝軟體再自行搭配硬體,或是採購軟硬體整合的一體機,使用雲端服務算是最新的一種。不過,從臺灣的角度來看,雲端服務模式與軟體導向解決方案,都不是企業最偏愛的選擇,相較之下,以硬體形式推出的一體機(Appliance)是最受青睞的一種。由於一體機的發展,已經轉向MPP架構,因此,使用者可以漸進式導入,後續再視巨量資料發展需求彈性調整,除了可以橫向擴充提升系統效能之外,也可以針對非結構資料處理,另外搭配Hadoop專屬平臺來處理。目前各個資料廠商已經逐步向Hadoop靠攏,並且從分庭抗禮轉為相互依賴的發展格局,Hadoop一體機因此相繼問世,對使用者來說,將可降低部署Hadoop叢集的門檻。
2012.05.24 於 「Big Data Taiwan 2012」的 Keynote 講稿。
主講者:Etu 副總經理/ 蔣居裕
《議題簡介》
無論是企業區域網路,還是開放的網際網路,在巨大的結構化與非結構化資料的背後,其實充滿著各種行為意圖,以及人、事、物、時、地的多維度關聯。商業的日益競爭,已經來到了一個除了講求行銷創意,還要擁有巨量資料處理與分析技術,才能出奇制勝的時代。有人形容 Big Data 的價值挖掘,就像是在攪拌混凝土,若在尚未完成前就中斷,將導致前功盡棄,全無可用的窘境。對 Big Data 的意圖與關聯探索,必須是 End-to-End 全程的照料,方得實現。本議程將舉例說明這個有序到永續的過程,讓聽者更能領略意圖與關聯充滿的世界。
Modernising Data Architecture for Data Driven Insights (Chinese)Denodo
Watch full webinar here: https://bit.ly/3phVEEv
In an era increasingly dominated by advancements in cloud computing, AI and advanced analytics, it may come as a shock that many organizations still rely on data architectures built before the turn of the century. But, that scenario is rapidly changing with the increasing adoption of real-time data virtualization - A paradigm shift in the approach that organisations take towards accessing, integrating, and provisioning data required to meet business goals.
As data analytics and data-driven intelligence takes center stage in today’s digital economy, logical data integration across the widest variety of data sources, with proper security and governance structure in place has become mission critical.
Register this webinar to learn:
- How you can meet the challenges of delivering data insights with data virtualization
- Why Data Virtualization is increasingly find enterprise-wide adoption
- How customers are reducing costs and delivering faster insight
Advanced Analytics and Machine Learning with Data Virtualization (Chinese)Denodo
Watch full webinar here: https://bit.ly/3mLNJ1J
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Attend this webinar and learn:
- How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo
- How you can use the Denodo Platform with large data volumes in an efficient way
- How Prologis accelerated their use of Machine Learning with data virtualization
海量計算的學習歷程分析與雲端資料庫管理系統Sqlmr appliance一體機開發計畫書 20140101Jackie Liu
硬體形式的一體機(Appliance)
End-to-End Big Data Solution in a Box
因應巨量資料處理需求,使用者大致上有幾個不同部署型態選擇,除了採用套裝軟體再自行搭配硬體,或是採購軟硬體整合的一體機,使用雲端服務算是最新的一種。不過,從臺灣的角度來看,雲端服務模式與軟體導向解決方案,都不是企業最偏愛的選擇,相較之下,以硬體形式推出的一體機(Appliance)是最受青睞的一種。由於一體機的發展,已經轉向MPP架構,因此,使用者可以漸進式導入,後續再視巨量資料發展需求彈性調整,除了可以橫向擴充提升系統效能之外,也可以針對非結構資料處理,另外搭配Hadoop專屬平臺來處理。目前各個資料廠商已經逐步向Hadoop靠攏,並且從分庭抗禮轉為相互依賴的發展格局,Hadoop一體機因此相繼問世,對使用者來說,將可降低部署Hadoop叢集的門檻。
2012.05.24 於 「Big Data Taiwan 2012」的 Keynote 講稿。
主講者:Etu 副總經理/ 蔣居裕
《議題簡介》
無論是企業區域網路,還是開放的網際網路,在巨大的結構化與非結構化資料的背後,其實充滿著各種行為意圖,以及人、事、物、時、地的多維度關聯。商業的日益競爭,已經來到了一個除了講求行銷創意,還要擁有巨量資料處理與分析技術,才能出奇制勝的時代。有人形容 Big Data 的價值挖掘,就像是在攪拌混凝土,若在尚未完成前就中斷,將導致前功盡棄,全無可用的窘境。對 Big Data 的意圖與關聯探索,必須是 End-to-End 全程的照料,方得實現。本議程將舉例說明這個有序到永續的過程,讓聽者更能領略意圖與關聯充滿的世界。