These tools provide users leverage to develop and interact with climate data sources. The ‘Models and Tools’ sheet collects analytics models that process/model raw data with output, such as synthesized indexes, hazard impact prediction, and assessment of risks related to climate, environment, and public health.

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Tech Accelerate tool is a free, comprehensive assessment of technology use and policies designed to help nonprofit staff with decisions, planning, and investments. The tool offers a single comprehensive assessment that provides multiple options for analysis and application. Organizations have used Tech Accelerate reports to apply for grants or support fundraising, inform strategic planning or budgeting, and build a technology roadmap. 

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People need technology to make sense of data and to present it in a digestible way. That’s where web and app analytics tools come in. The tools described in this resource gather and visualize data to help people make meaningful decisions.

The post Selecting the Right Data Analytics Tools for Your Nonprofit appeared first on data.org.

Social impact organizations (SIOs) can find sample code, templates, and other assets from across the Microsoft ecosystem. This GitHub repo provides lightweight solutions, such as a damage assessment visualizer, an open data community kit, and a data sharing accelerator, that are ready to use and easy to adapt — and is continually updated by the Tech for Social Impact team.

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Artificial intelligence (AI) is on the brink of a boom. It’s now guiding decisions on everything from crop harvests to bank loans, and uses like fully automated customer service are on the horizon. The key is to understand the organizational and cultural barriers AI initiatives face and work to lower them. This resource provides guidance for organizations to get started with implementing AI in their operations and workflow.

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In taking on urgent global challenges, organizations are faced with a critical hurdle: a lack of necessary data. There are many ongoing efforts to fill this data gap, including developing new technologies, sources, and collaborations. But promising data-sharing partnerships and data collaboratives (particularly between the private and public sectors) can struggle to overcome institutional and legal barriers.

This resource provides both an analytical framework and an online library of legal clauses that capture the key elements of sharing agreements for data collaboration, complete with links to several detailed guides. This resource addresses the lack of clarity around data sharing and data action issues that often result in high transaction costs and significant delays during the negotiation process.

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Creating a data culture is one of the keys to building a data-driven organization. The right technology, data literacy, and disrupting the status quo are ways to start, with the understanding that people are at the core of any data culture transformation. While transformations can be difficult, the value of embracing data is clear: data-driven companies enjoy increased revenue, improved customer service, best-in-class operating efficiencies, and improved profitability. This article talks about steps leaders can take to build a data-driven culture.

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Cloud, open-source, and SaaS business models have transformed the software industry and how companies think about and build their products. Today, users can set up an entire technology stack in a fraction of the time and cost than before. And it’s no surprise that these transformations have paved the way for the modern data stack.

Typically, modern data stacks are built on cloud-based services, and increasingly include low- and no-code tools that empower users to explore and use data. This guide provides recommendations for organizations to create modern technology stacks to store, manage, and analyze their data.

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Increasing numbers of nonprofits are utilizing data visualization to present results, successes, and accomplishments to their donors and investors. Nonprofit data visualization can effectively impact and motivate an audience, change minds, and spark action. This resource provides an introduction to data visualization, including best practices, use cases, and types of visualizations to enhance data storytelling.

The post Let’s Get Visual: Nonprofit Data Visualization appeared first on data.org.

Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram, or map.

The field of data visualization combines both art and data science. While data visualization can be creative and pleasing to look at, it should also be functional in its visual communication of the data.

This resource explains the fundamentals of data visualization, including examples of different types of data visualizations and when and how to use them to illustrate findings and insights.

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Data science and machine learning (ML) platforms are cohesive software applications that offer a mix of basic building blocks essential for creating many kinds of data science solutions and incorporating such solutions into business processes, surrounding infrastructure, and products. This resource provides organizations with peer reviews and ratings of data science and ML platforms they can purchase for use.

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Data visualizations are arguably the most effective way to translate large amounts of information into bite-sized pieces that are easy for a broader audience to digest. Just as cooking combines various ingredients to create a memorable experience through a particular meal, data visualization can bring together many different pieces of information into a central — and memorable — format. This resource provides guidance on how nonprofits can create data visualizations to demonstrate their impact.

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