Take - 451 188宝金博网址是多少Research -分析企业IT创新的业务 所有标记为451 Take的博客条目//www.billcordell.com/blog/tags/187-451-take 2022年6月17日星期五12:56:41 +0000 en - 播客:冠状病毒大流行期间的互联网状况 //www.billcordell.com/blog/2001-podcast-state-of-internet-amid-coronavirus-pandemic //www.billcordell.com/blog/2001-podcast-state-of-internet-amid-coronavirus-pandemic 由于冠状病毒大流行导致国家处于关闭模式,家庭媒体使用量飙升,学生和远程工作人员的带宽消耗也增加了。senior analyst at 451 Research, and John Fletcher, a media analyst at Kagan - a research unit within S&P Global Market Intelligence, who were both recent guest speakers on the latest episode of "MediaTalk," an S&P Global Market Intelligence podcast.
admin@www.billcordell.com(卡珊德拉·罗) 研究与数据 2020年6月11日星期四15:08:29 +0000
视频:企业数字脉冲冠状病毒快速调查的声音 //www.billcordell.com/blog/2000-video-vote-digital-pulse-coronavirus-flash-survey //www.billcordell.com/blog/2000-video-vote-digital-pulse-coronavirus-flash-survey < span style=" font - family:宋体;保证金:汽车;class="vidyard-player-embed" src="https://play.vidyard.com/bxRHazJm3kQeSWb7ezBnDt.jpg" data-uuid="bxRHazJm3kQeSWb7ezBnDt" data-v="4" data-type="inline" />
In my  企业之声:数字脉搏,冠状病毒闪电调查,我们衡量了大流行对企业运营和战略的影响。我们在上面的视频中总结了一些主要发现,包括我们的“451 Take”,但您可以在标普全球市场情报网站上查看更多见解。随着疫情的持续影响,我们将在这个COVID-19微型网站上分享我们所有面向公众的见解。
admin@www.billcordell.com(卡珊德拉·罗) 研究与数据 2020年5月4日星期一20:18:53 +0000
2020年1月1日至3月16日的热门报告 //www.billcordell.com/blog/1997-top-reports-from-january-1-march-16-2020 //www.billcordell.com/blog/1997-top-reports-from-january-1-march-16-2020 以下是自2020年第一季度开始以来我们公开提供的报告摘要列表。451 Research的仪表板中提供的内容远不止以下内容。188宝金博网址是多少登录或申请试用访问,浏览所有451内容。应用基础设施&;企业网络自动化获得竞争优势管理服务研究20188bet金博宝是什么20年云趋势:复杂性之年及其管理人才驱动管理服务机会如何导航451的云原生研究2020年旧的管理服务和海洋:2020年云经济趋势商业研究:数字钱包的采用:商家和消费者的视角数据,人工智能&;分析研究基于云的人工智能平台对企业的重要性AI451视角:持续智能成为实时分析数据中心服务的继任者188bet金博宝是什么基础设施研究特色数据-阿拉伯联合酋长国:租赁数据中心市场2020年推动多租户数据中心和服务行业的趋势信息安全研究对云安全风险的认知正在改变物联网研究巨大的人员变化:人口结构的定时炸弹推动工业物联网、增强现实和人工智能的采用边缘和云应用的游戏行业的演变和复杂性劳动力生产力和188bet金博宝是什么协作研究冠状病毒将破坏您的员工队伍:确保您为远程工作人员制定正确的工具策略冠状病毒将破坏您的员工队伍:以下是减轻业务影响的10种方法2020年您需要了解的10种员工生产力和协作趋势2020年it趋势下载我们2020年预览报告的免费摘录我们在2月份完成了2020年预览网络研讨会系列。所有的网络研讨会都可以在这里观看。 admin@www.billcordell.com(卡珊德拉·罗) 研究与数据 2020年3月16日星期一03:04:28 +0000 你的人工智能基础设施准备好满足未来的需求了吗? //www.billcordell.com/blog/1996-is-your-ai-infrastructure-prepared-to-meet-future-demands //www.billcordell.com/blog/1996-is-your-ai-infrastructure-prepared-to-meet-future-demands 图1 ai的企业基础架构状态 //www.billcordell.com/blog/1988-taking-a-new-approach-to-unstructured-data-management //www.billcordell.com/blog/1988-taking-a-new-approach-to-unstructured-data-management 作者:Steven Hill -高级分析师,应用基础设施和存储技术- 451 research企业存储从来都不是一件容易的事。188宝金博网址是多少业务依赖于数据——所有的数据都是从存储开始和结束的——但是我们处理数据的一般方式,特别是非结构化数据的方式,并没有像IT行业的其他部分那样真正发展起来。当然,我们已经大大提高了存储的速度和容量,但我们还没有处理由于性能和密度的提高而导致的存储增长的实际问题;更不用说管理数据增长的挑战了,现在数据增长跨越了世界各地的多个混合存储环境。事实是,你无法控制你看不到的东西;因此,越来越多的企业支付了大量的资金来反复存储相同数据的多个副本。或者更糟糕的是,保留相同数据的多个版本,而它们之间根本没有任何引用。多个存储平台之间的大量数据碎片可能是不受控制的存储增长的主要来源之一;除此之外,“保留一切”的数据管理方法还会带来新的风险。基于隐私的举措,如欧盟的GDPR和加州的CCPA-2018,要求对许多垂直市场的存储策略进行全面重新评估,以确保符合这些新法规,以根据需要保护、保护、交付、编辑、匿名化和验证包含个人身份信息(PII)的数据的删除。 While this can be a more manageable problem for database information, it’s a far greater challenge for unstructured data such as documents, video and images that make up a growing majority of enterprise data storage. Without some form of identification this data goes “dark” soon after it leaves the direct control of its creator, and initiatives like GDPR don’t make a distinction between structured and unstructured data. There can be a number of perfectly good reasons for maintaining similar or matching data sets at multiple locations, such as data protection or increased availability. The real challenge lies in being able to maintain policy-based control of that data regardless of physical location, while at the same time making it available to the right people for the right reasons. Documents and media such as images, audio and video are making up a growing percentage of overall business data, and companies have a vested interest in making continued use of that data. But at the same time, there can be serious legal ramifications for not managing all this data properly that could potentially cost companies millions.The cloud has changed the IT delivery model forever; and with a hybrid infrastructure, business IT is no longer limited by space, power and capital investment. The decisions regarding workload and data placement can now be based on the best combination of business needs, economics, performance and availability rather than by location alone; but with that freedom comes a need to extend data visibility, governance and policy to data wherever it may be. In this context, the problems of data fragmentation across multiple systems are almost inevitable; so, it really comes down to accepting this as a new challenge and adopting next-generation storage management based on an understanding of what our data is, rather than where it is. Mass data fragmentation is a problem that existed before the cloud, but fortunately the technology needed to fix this is already available. From an unstructured data perspective, we believe this involves embracing a modern approach that can span data silos for backups, archives, file shares, testing and development data sets and object stores on that bridges on-premises, public cloud and at the edge. A platform-based approach can help to give you visibility into your data, wherever that data resides, and more importantly, can help you maintain greater control by reducing the number of data copies, managing storage costs, and ensuring your data stays in compliance and backed up properly. We also think an ideal solution seamlessly blends legacy, file-based storage with the management flexibility and scalability offered by metadata-based object storage. This requires a fundamental shift in the way we’ve addressed unstructured data management in the past; but it’s a change that offers the benefits of greater data availability and storage-level automation and provides a new set of options for controlling and protecting business data that’s both a major business asset and a potential liability if not handled correctly.  admin@www.billcordell.com(卡珊德拉·罗) 研究与数据 2019年6月27日星期四18:15:28 +0000