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More data, more problems
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Acknowledging the problems that massive amount of data poses to your organization is going to be step one in proper classification.
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Problem 1: Lack of visibility into a growing dataset
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Your organization collects and generates a massive amount of data across different systems in a variety of forms. Before you can establish and enforce policies to promote usability, secure data, and maintain compliance, you must understand what data you have and WHY you have it.
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Problem 2: Need to reconcile data risk and reward
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Because of this relationship, you’re always on the hunt for technology that helps your business understand the data it has, the risks it poses to the business, external requirements (compliance) related to data, as well as the internal initiatives and expectations related to it.
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Problem 3: Time to market
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Your business needs to be able to find sensitive data, highlight where it lies, and be able to quickly take remediation efforts in the event of a security incident.
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The average volume of data held by an enterprise grew by 42% last year. One of the biggest challenges stemming from this explosion of data is insider access. Does your company know how to monitor and manage this type of data sprawl? Join this webinar to learn more.
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What is data access governance?
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The key objective of data access governance is to gain visibility into risk and enforce data access policies. Data access management has evolved into an independent initiative that requires an autonomous strategy, budget, and implementation schedule. Data access governance covers many crucial areas, including data security; protecting PII; providing access to critical data assets; and managing permissions.
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What is dark data?
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Dark data is the information assets an organization collects, processes, and stores during regular business activities, but generally fails to use for other purposes. For example, dark data could come in the form of analytics, business relationships, and direct monetization.
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Who is a data citizen?
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A data citizen is an employee who is given access to an organization’s proprietary information. Use of the word “citizen” is meant to emphasize the idea that an employee’s right to access corporate data also comes with responsibilities.
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What is a data estate?
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A data estate is simply the infrastructure to help companies systemically manage all their owned corporate data.
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What is data minimization?
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Data minimization is a principle that states data collected and processed should not be held or further used unless this is essential for reasons that were clearly stated in advance to support data privacy.
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What is Data Security Posture Management?
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Data Security Posture Management (DSPM) is an emerging market focused on reducing risk and improving the security around an organization’s most valuable asset – its data.
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What is Data Sprawl?
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Data sprawl is the proliferation in the number and different kinds of digital information (data) created, collected, stored, shared, and analyzed by businesses, primarily at the enterprise level. On average, organizations have four-to-six platforms to manage data.
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What is ROT Data?
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Redundant, obsolete, or trivial (ROT) data is the digital information a business has despite the data having no business or legal value, i.e. a duplicated piece of information or data point that doesn’t help the company in any positive way.
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In order to cull and manage ROT data, your business needs a data retention and deletion strategy. Join this webinar for tips and best practices on ensuring ROT data isn’t hindering your business.
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Shift left: A data classification strategy
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Data discovery has as much to do with classifying its whereabouts and importance as it does what actions should ultimately be taken with that digital information. Forward-looking security should be employing the shift left strategy. But what exactly does that mean?
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Shift left is a philosophy that looks at data ingestion at the left side of a horizontal funnel (see image). According to IAPP, that narrow end represents the point when data first enters the company’s tech ecosystem. As you move right in the funnel, the amount of data grows with copies, inferences, and data analysis. The point of collection is best suited to classify and inventory data, creating downstream efficiencies. Most companies classify and inventory data toward the right side of the funnel, which is a recipe for delays, inaccuracies, and potential security incidents.
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更多的数据,更多的问题
承认问题,大量的数据对您的组织将是第一步在适当的分类。
问题1:缺乏可见性不断增长的数据集
组织收集和生成大量的数据在不同的系统在不同的形式。才能建立和实施政策促进可用性、安全数据,并保持一致性,您必须了解哪些数据,为什么你拥有它。
问题2:需要调和数据风险和回报
因为这个关系,你总是在寻找技术,帮助您的业务理解的数据,它对业务风险,外部需求(合规)相关数据,以及相关的内部活动和期望。
问题3:上市时间
你的业务需要能够找到敏感数据,突出它在哪里,并能够迅速采取补救措施在发生安全事故。
的平均体积数据由一个企业去年增长了42%。最大的挑战之一源于这爆炸的数据内部访问。贵公司知道如何监控和管理这种类型的数据扩张?加入这个网络研讨会,学习更多的知识。
数据访问管理是什么?
数据访问控制的主要目标是获得可见性风险和执行数据访问政策。数据访问管理已经发展成为一个独立的行动,需要自主策略,预算和实施计划。数据访问管理涵盖了许多关键领域,包括数据安全;PII保护;提供关键数据资产;和管理权限。
黑暗是什么数据?
黑暗组织收集数据的信息资产,流程,和商店在正常业务活动,但通常不能用于其他目的。例如,黑暗的数据可能会的形式分析,业务关系,直接货币化。
一个数据公民是谁?
数据的公民是一个员工,他得到一个组织的专有信息。使用“公民”一词是强调员工的权利访问企业数据也有责任。
什么是数据房地产?
数据房地产只是基础设施来帮助企业系统管理所有拥有企业数据。
什么是数据最小化?
最小化原则,国家数据收集和处理不应该举行或进一步使用,除非这是至关重要的原因是事先明确表示支持数据隐私。
什么是数据安全的姿势管理?
数据安全姿势管理(DSPM)是一个新兴的市场集中在降低风险和改善周围的安全组织的最有价值的资产——它的数据。
什么是数据扩张?
数据蔓延扩散在数量和不同种类的数字信息(数据)创建、收集、存储、共享和分析业务,主要在企业级别。平均4 - 6平台组织管理数据。乐动平台登录链接在哪
腐烂的数据是什么?
冗余的、过时的或微不足道(腐烂)数据是数字信息业务,尽管数据没有商业或法律价值,即一个复制的信息或数据点,并不在任何积极的方式帮助公司。
为了收集和管理腐败数据,您的业务需要一个数据保留和删除策略。加入这个网络研讨会技巧和最佳实践确保腐烂数据并不是阻碍你的业务。
左移位:数据分类策略
分类数据发现尽可能多的与它的位置和重要性,最终应采取什么行动数字信息。前瞻性的安全应该采用左移位的策略。但这到底意味着什么呢?
左移位是一种哲学,看数据摄入水平的左边漏斗(见图片)。根据IAPP,狭窄的结束代表着当数据第一次进入公司的科技生态系统。当你移动的漏斗,与副本的数据量增长,推理和数据分析。收集的重点是最适合分类和库存数据,创建下游效率。大多数公司分类和库存数据的右侧漏斗,导致延迟,错误,和潜在的安全事故。
