A big element of trust building in #Data and #Analytics is your ability to explain and justify every technical and non-technical decision you make in building the #Algorithm. #Statistics #DataScience #MachineLearning #AdvancedAnalytics #AI
关于我们
Let's figure out the people, process, management, and governance of data and analytics where the vast majority go wrong before even getting to the technical stuff. We help organizations and professionals at all levels--executive leaders, managers, and individual practitioners--by providing critical strategic advisory, coaching, and training on the non-technical aspects of data and analytics.
- 网站
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https://www.msightanalytics.com
Msight Analytics, LLC的外部链接
- 所属行业
- 商务咨询服务
- 规模
- 1 人
- 总部
- Palm Harbor，FL
- 类型
- 私人持股
- 创立
- 2014
- 领域
- Management Consulting、Data、Analytics、Statistics、Data Science、Machine Learning、AI、Data Management、Data Quality、Data Governance、Analytics Governance、AI Governance、Advanced Analytics、Information Services和Information Management
地点
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主要
获取路线
US，FL，Palm Harbor，34684
Msight Analytics, LLC员工
动态
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A good part of the problem with bias in #Analytics is related to the lack of understanding about how the #Algorithm does what it does. #Data #Statistics #DataScience #MachineLearning #AdvancedAnalytics #AI
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For one to make informed decisions, one must be *willing* to make informed decisions. There are two aspects to the willingness to use #Data in decision-making: appetite and trust. #Analytics #Statistics #DataScience #MachineLearning #AdvancedAnalytics #AI
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When #Data and #Analytics start at the position of trust deficit, the lack of explanation or our inability to explain just gives others more reasons to distrust analysts and analytics. #Statistics #DataScience #MachineLearning #AdvancedAnalytics #AI #BI
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Rarely do we focus on eliminating reasons for distrust in #Data. Seemingly inconsequential details often cause people to lose trust not just in the analytic at hand but in #Analytics more generally. #Statistics #DataScience #MachineLearning #AdvancedAnalytics #AI #BI
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In practice, #Analytics starts at the position of trust deficit; many are primed to distrust it at the first sign. We practitioners do ourselves a disservice by starting with the presumption that people are trust-neutral about #Data. #Statistics #DataScience #MachineLearning #AI
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If we cannot explain it, we do not know what we have built. While nothing can be guaranteed risk-free, we need due diligence that our #Analytics products do not cause harm or cause others to do harm. #Data #Statistics #DataScience #MachineLearning #AdvancedAnalytics #AI #AIEthics
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What is the future of the #Analytics profession? What *really* makes humans different from #AI? "The value of humans in the world of AI" ? https://bit.ly/4gYbONT #Data #Statistics #DataScience #MachineLearning #AdvancedAnalytics
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Explaining and justifying technical concepts in #Analytics is challenging. But we have an obligation to the users of our products to know what we are doing. This is independent of whether and how much of that is disclosed. #Data #Statistics #DataScience #MachineLearning #AI
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All #Analytics practitioners should be able to articulate what they have built, how they built it, why they built it the way they did, & why every decision along the way makes sense. Even if it is to an imaginary audience. #Data #Statistics #DataScience #MachineLearning #AI