2019-02-02 夜深了，，，春节了，除了吃喝玩乐，也学学人家写写PPT！！！新东方教育集团，不单单教你学英语，还教职业法则：“干活的累死累活，到头来干不过写PPT的”。。。那么，那些写PPT的都在看什么呢？不会只看公众号，人云亦云吧？其实，那些真正会写PPT的，往往大量阅读各种业界咨询报告。。。其中以Gartner的报告最受欢迎!【1979年成立的Gartner乃是IT研究与顾问咨询公司的老大】其每年发布的魔力象限【Magic Quadrant】是所谓的必杀技！
权威的Gartner，前两天刚发布了 2019 Magic Quadrant for Data Science and Machine Learning Platforms【点击获原文】洋洋洒洒快五十页！里面讲述了数据科学和机器学习平台的最新研究和行业调查！特别概述了2018年全年的发展和变化。。。2018年是AI被重新审视的一年，数据科学和机器学习是AI最贴近各大企业的AI分支，这份报告的内容显得意味深长。期间多次提及了开源战略和Apache Spark。对基于Apache Spark的砖厂【Databricks】不吝赞美之词。【靠客观中立吃饭的Gartner的研究论述不可能是软文】这个战场，充满着财力雄厚人才济济的IT巨头【Microsoft，Google，IBM，SAS】，砖厂能异军突起，实属不易！如今排名前列的其他几家还停留在小数据分析的过去，而砖厂专注的却是最热的大数据分析。字里行间，Gartner对我们砖厂的眼光，战略和决策的相当肯定！Databricks: Unified Analytics Platform!
关于砖厂的描述：
Databricks (https://databricks.com/) is based in San Francisco, U.S. Its Apache Spark-based Unified Analytics Platform combines data engineering and data science capabilities that use a variety of open-source languages. In addition to Spark, the platform provides proprietary features for security, reliability, operationalization, performance and real-time enablement on Amazon Web Services (AWS). Azure Databricks, which became generally available in March 2018, is an integrated service within Microsoft Azure that provides a high-performance Apache Spark-based platform optimized for Azure.
Databricks remains a Visionary by providing support for the end-to-end analytic life cycle, hybrid cloud environments and accessibility for a wide variety of users. A focus on innovation and a consistently strong and comprehensive product offering have enabled Databricks to improve its position for both Ability to Execute and Completeness of Vision.
■ Innovation [创新力]: Breadth and ease of open-source integration, streaming IoT capabilities and operationalization capabilities are key differentiators for Databricks. Its platform extends on open-source capabilities by providing the framework needed for end-to-end enterprise scalability, performance and operationalization. Databricks Delta, launched in October 2017, provides a managed cloud service for unified data management with support for streaming analytics and ML. MLflow, launched in June 2018, includes support for experimentation, reproducibility and deployment. The Databricks Runtime for Machine Learning provides preconfigured clusters for deep learning.
■ Partnership with Microsoft [微软联盟]: Azure Databricks has quickly gained traction within the Azure community. Azure Databricks adds global scale to Databricks’ effective marketing and sales strategy. It includes an interactive, collaborative workspace for collaboration between data scientists, data engineers and business analysts, single click-to-launch Spark environment capability, and integration with Azure components.
■ Customer appreciation [客户认同]: Surveyed reference customers scored Databricks in the top quartile for both customer experience and operations. Databricks received the highest overall scores for both overall vendor experience and quality of documentation.
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