如何信任数据?

Among executives, 78% have problems using data to make decisions, according to a 2021年数据健康调查. Even in a world that seems flooded with data and reports, business leaders still can’t—or don’t—apply the data when making their decisions. 为什么? 50% rated data quality as the leading challenge. They simply don’t know if they can trust the data.

In the eyes of these stakeholders, consistency and completeness of data is never guaranteed. Its timeliness and relevance are also sometimes in question. And even when data is reliable, it may not be easily accessible. Is it any surprise that executives are sometimes ignoring data and going with their gut?

The same qualities that make data unreliable for humans make it unreliable for artificial intelligence. AI adoption is growing around 9% annually, with 56% of respondents to a 2021年麦肯锡全球人工智能调查 reporting they use artificial intelligence in at least one function.

This means that even though 78% of executives aren’t able or willing to use data to inform their own decisions, artificial intelligence platforms are being invested in to drive excellence with the same unreliable data.

How can you get to a place where you trust your organization’s data, for decisions made by both humans and automation? MG游戏登录网页 is providing tips and guidance to extract more value from your data in our latest blog.

mg官方游戏中心为什么相信数据?

Businesses trust in data and take action on it despite suspecting its flaws because they know that even flawed data holds insights and efficiencies. 即使数据并不完美, it can still reveal trends and patterns in customer acquisition and retention, 市场营销, 用户采用, 以及其他领域. When businesses have already achieved success in these areas, AI helps transfigure those wins into repeatable processes.

But when the underlying data informing AI is not properly governed and managed, 这些胜利充其量是有限的. 在最坏的情况下, bad data can lead to bad decisions and increased risk, while bad 数据管理 can lead to 安全 breaches and losses of consumer trust.

For AI to truly work—and for employees to trust the predictions it provides—the data underlying it must be clean, 有组织的, 和安全. 更重要的是, the steps an organization has taken to clean 和安全 the data must be communicated to end users, not just the data analysts and those who provide data.

信任数据意味着什么?

For many, trusting data means getting past concerns about data bias. Data bias is the fact or perception that the available data is not actually representative of reality. Everything from a small survey size to missing variables to label bias based on gender, 比赛, or other societal factors are all forms of data bias. In human users, knowledge of these gaps means they may not take data seriously. 在人工智能领域, these biases can lead to inaccurate forecasts and skewed recommendations because the perspective driving the algorithm is limited.

The answers to concerns about data bias are processes of data integrity and data governance.

数据完整性

Data with integrity is accurate and reliable. Data can have both physical and logical integrity. The physical integrity of data refers to how it is stored and who has access to it. The logical integrity is whether the data is complete and accurate in and of itself. Data which includes factors of societal bias, 例如, would be considered to lack logical integrity, because the stereotypes in the data are inaccurate. Data integrity is preserved through clear rules about data entry and validation, including validating the practices of third parties who provide data.

数据治理

Data governance is the cross-enterprise process(es) for ensuring data integrity, 安全, and that data is being used as intended. Data governance programs must be focused on the business goals a company is seeking to achieve by leveraging data. 这可能是更多员工的支持, better performance on annual compliance, or improved relationships with high-value customers. Data governance programs achieve these aims by breaking down departmental data silos. This helps reveal inconsistencies and potential errors in data, while also giving decision-makers access to the full set of insights available to the business.

For decision-makers, trusting data means being confident it is accurate and reliable. This confidence requires at least partial understanding of the processes and procedures that have led to that state of data quality. 没有人喜欢被告知“相信它”,” and when that is all people have to go on, 他们很少分享彼此的信任.

If you are looking for guidance and support to clean up your data and better-communicate your data initiatives to employees, MG游戏登录网页 is the partner for you. mg官方游戏中心的专家团队 与内部员工合作 to teach them how to clean up data, look for signs data is in trouble, and develop and communicate 数据治理技术 这是定制适合您的业务. 你可能还不相信你的数据, but you can trust MG游戏登录网页 to help you get to that ideal state. 立即mg官方游戏中心 开始对话!