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Open for comment: Proposed changes to Candid’s taxonomy

Candid

Every year, Candid processes data on nearly two million organizations and more than three million grants. That data makes its way into various products and services to help: nonprofits find funding; researchers, advocates, and journalists derive insights into what is happening in the sector; and all types of funders to make funding decisions.

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Top Ten Data Challenges (And Solutions) for Associations

Association Analytics

But when it comes to a troubling relationship with your data, can you turn to those same people? If you’re struggling to find someone to share your data woes with, we’re here to help you decipher the signs and get you back on track. Older models tended to be AMS-centric, leading to siloed data, static reports, and that trapped feeling.

professionals

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AI at Candid: Powering technology to support the sector’s lasting success

Candid

Generative AI products, such as ChatGPT, are examples of a branch of AI called machine learning, which is concerned with learning from data to surface trends and predictions. In this blog, I will first explain how Candid currently harnesses the power of AI technologies in our data and tools. million nonprofits worldwide.

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New and Improved Data Visualization Tool: Maps for Media Funding

Beth's Blog: How Nonprofits Can Use Social Media

Nonprofit data nerds will love this new resource from Media Impact Funders and Foundation Center called “ Foundation Maps for Media Funding ,” a free, interactive mapping and research tool that shows the full scope of philanthropically funded media projects worldwide since 2009. Click to See Visualization.

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Community colleges: A critical access point to higher education

Candid

The plan includes a proposal to allocate $109 billion for two years of free community college for all Americans, including Dreamers. . billion in grants specifically for “community college education,” according to Candid data. The proposal for free community college has garnered bipartisan support, for the most part.

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