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Why your association needs to adopt a data governance policy

Nimble AMS

Does your association have a data governance policy? In our data-driven world, governance is crucial in maintaining the integrity, accuracy, and security of your organization’s data. What is data governance? . Why does your association need a data governance policy? .

Policy 117
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From Data Deluge to Impactful Decisions: Mastering Data in Grantmaking

sgEngage

Applications, proposals, progress reports, impact metrics – the data collected throughout the grantmaking lifecycle is vast and ever-growing. While this data holds immense potential to improve decision-making and maximize impact, harnessing its power can be a challenge.

Data 72
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Why your organization needs to reinvest in the state of its member data

Nimble AMS

What is the state of your member data? According to Community Brands 2022 Association Trends Study, while data analytics is a higher priority for organizations, just one-third of association professionals report their data is excellent or very good. Reporting on the state of member data. What’s causing this disconnect?

Data 139
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Don’t Fear Your Dirty Data

Association Analytics

The concept of “dirty data” and how to approach it can be daunting. Simply put, dirty data is data that is inaccurate, incomplete, inconsistent, duplicative, or outdated. At Association Analytics, we sometimes hear concerns about data quality in the context of associations starting their journey into analytics.

Data 169
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Digital Transformation for Government Agencies

Forum One

Digital transformation or modernization for government agencies is about using new technologies to effectively change an agency’s ability to engage audiences and achieve its mission. Common challenges in government digital transformation pursuits include overlapping or redundant solutions and processes and siloed teams and communications.

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Advancing Racial Equity Through Data and Transparency

sgEngage

The first iteration tracks disclosure of 22 data points across six specific dimensions of racial equity: (1) Pay Equity, (2) Racial/Ethnic Diversity Data, (3) Education and Training Programs, (4) Response to Mass Incarceration, (5) Community Investments, and (6) Anti-Discrimination Policies.

Data 95
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Experts Weigh In: Applying Artificial Intelligence (AI) and Machine Learning (ML) for Government

Forum One

I find the rapid developments in Artificial Intelligence (AI) and Machine Learning (ML) thrilling, with endless applications for our Forum One partners, but I know from discussions with my counterparts in government agencies that AI and ML can also be mystifying, and even scary. ‍Jay earned a B.A.