数据治理

通过数据资产治理实现一致的数据管理

Effective data governance is essential for businesses to gain valuable insights from their data and mitigate risks related to data quality, 隐私, 和安全.

数据质量: 数据质量是确保数据准确的数据治理的关键要素, 一致的, 而且质量高. This involves establishing clear standards for data quality and ensuring that data is regularly monitored and 维护.
数据所有权: Data ownership is another important element of data governance that defines who is responsible for managing and maintaining data. 这包括为数据所有权建立明确的角色和责任, 确保数据得到妥善保护.
主数据管理: Master data management is the process of managing the core data elements that are essential to an organization’s operations.
数据的可发现性: Data discoverability is the process of making data easily accessible and discoverable by stakeholders within an organization.

通过有效地管理这些数据治理的核心元素, 企业可以确保他们的数据准确无误, 安全, 、有序. This enables them to make informed decisions, mitigate risks, and drive growth and innovation.

什么是数据治理?

的数据治理研究所将数据治理定义为 与信息有关的过程的决策权和责任体系, executed according to agreed-upon models which describe who can take what actions with what information, 当, 在什么情况下, 用什么方法.

数据治理 是一套政策吗, 程序, 以及管理数据收集方式的标准, 存储, 和管理.

数据质量维度vs. 指标

我们利用 企业数据管理框架 了解当前的人员、流程、技术和数据.

企业可以设置基准来简单地衡量数据的质量.
的se dimensions and metrics allow for business leaders to determine justifiable levels of data quality based on the most important business factors (data timeliness, 缺失的数据, 数据类型不正确).

维 are categories of data quality issues with a shared reason why they are important and often have similar underlying causes.

为什么我仓库里的数据不是最新的?
为什么我的操作工具中的数据落后了六个小时?
为什么我的仪表盘需要这么长时间才能刷新?

指标描述一个尺寸是如何测量的, 数量上的或质量上的, 并且可以随时间追踪.

仪表板访问时间与数据最近刷新时间的差异
未满足服务水平协议的小时数
ELT负载和反向ETL操作之间的平均延迟

什么是主数据管理(MDM)?

通过主数据管理实现数据一致性管理

主数据管理(MDM) 创建、维护和利用主数据的过程是跨组织的吗. 这个过程包括识别和定义主数据, 创建和维护主数据的中央存储库, 确保使用主数据的所有系统的数据质量和一致性.

数据一致性和数据质量: MDM helps ensure that data is 一致的 and accurate across different systems and applications. 它提供了一个, 关键业务数据的权威来源, 这样可以降低数据不一致和错误的风险.
节约成本: MDM可以通过消除数据冗余和提高数据质量来帮助降低成本. 这将导致更高效的流程、更少的错误和更低的操作成本.
法规遵从性: MDM can help organizations comply with industry-specific regulations by ensuring that data is accurate and complete.
统一的视图: MDM帮助组织创建客户、患者、设施等的统一视图. allowing the organization to understand their from a comprehensive perspective and ultimately, 更好的业务成果.

整体, MDM对于希望建立坚实数据基础的组织至关重要, 降低成本, 遵守法规, 改善决策, 推动商业成功.

为什么管理对数据可用性的控制对数据治理至关重要?

对数据可用性的管理控制将导致其治理的一致性, 哪一点对其可用性至关重要, 完整性, 和安全, 支持企业的增长和灵活性.

建立一个具有明确授权的管理机构或理事会, 目标, 流程将有助于确保一致性得到维护.
Automating your processes and enforcing the 程序 that have been established will support consistency.
跨部门共享数据的一致性, 例如客户号或零件号, 或供应商和员工id, 将删除重复数据并使数据标准化吗, 减少进入核心企业系统的不正确数据的数量. This will also greatly lessen the amount of chaos and confusion that can come from in一致的 data and information shared within a company.

Consistent data governance will allow your departmental management to make informed operational decisions, while strategic decisions that are made by the corporate management will be based on information that can be trusted as being a clear and correct snapshot of the operation. 一个版本的真相会让你的整个企业受益.

一致性数据治理的好处是什么?

Every group or department in your private equity organization is going to need their own view of your data. 例如, 如果他们关注的是年终销售, 重点将放在你的销售团队去年完成的所有业务上. 集团控制器将有不同的业务线需求, 并将查看所有已结案的业务，这些业务已记入总账. A portfolio company CEO will get a different answer to a query involving those year-end sales figures depending upon who he or she is asking. 的 private equity managing partner might like to look at each individual portfolio company or their entire portfolio rolled up to benchmark metrics. Establishing a common set of data parameters that your whole organization follows will not be simple, 但是一致的数据治理将给您的组织带来巨大的好处.

一致性数据治理的一些好处是:

减少花费在报告协调和不一致的性能结果上的时间.
由于在多个系统中手动输入数据，减少了数据输入错误
为整个企业的关键性能指标提供一致的定义集
数据一致地分布在整个组织中
更好地管理关键的公司主数据，例如添加/删除/更改
Eradication of bottlenecks in your change management process that can delay the approval of adds/deletes/changes
It will ensure accurate 程序 with relation to regulation and compliance activities and increase the transparency required in these areas.
数据的价值将会增加, 并支持过去和当前数据问题的解决方案.
的 costs that can be associated with other areas of data management will decrease and the overall revenue of your enterprise will increase.

为什么需要一个好的数据治理策略?

Your business will need a strong policy for your data governance so that as training and education practices around the management of your data assets is implemented, 组织内部的方向和遵从是清晰和一致的. A good data governance policy will help maintain effective processes when it comes to managing all the information of your business.

当你分析所有可能影响你业务目标的内部和外部因素时, a data strong and effective governance policy can be formulated which will determine the implementation of your strategy when it comes to handling your data and will help your enterprise gain better control over all your data assets, 包括方法, 围绕正确管理数据的行为和技术.

强大的数据治理策略会考虑您的目标. 为下面列出的每个领域建立目标和绩效指标:

在整个业务中定义与数据相关的关键角色. 对于每一个系统, choose stewards to manage that data and focus on quality; the owners who will make decisions and define quality standards, IT团队将提供技术支持并监控所有合规性.
Document and inventory all your sources for data and review the inventory regularly to ensure it is up to date.
的 purposes for which you collect data should be identified and communicated to your team and clients and reviewed regularly.
应该有适当的策略来定义如何创建记录, 维护, 然后处理掉.
质量和准入. Appropriate staff members should be assigned the responsibility for data quality and to conduct regular audits while all permissions and access should be clearly defined.
需要根据数据的访问和共享来定义数据安全策略. 包括概述风险和可能性的风险管理部分.

You want to know that the formal management of all the data assets within your organization is efficient and cost-effective and is bringing the most return on your investment possible. A well-thought out policy will do just that by ensuring that all your team members know who can take which actions, 要用什么方法呢, 在什么情况下, 减少由于方向不明确或可用信息不完整而浪费的时间.

您的策略如何定义您的业务将影响您管理业务的能力, 让每个人都保持专注和同步, 朝着同样的目标努力.

LBMC数据分析领导力

乔恩希尔顿

股东、咨询 & 商业智能

纳什维尔

布莱德米尔纳

高级主管，医疗保健分析