Data & Trust Alliance’s Post

I'm delighted to see the release of these groundbreaking #dataprovenance standards. These new standards are the first cross-industry standards and will increase transparency in the origins of the data used in traditional and #AI applications. #datagovernance Explore the Data Provenance Standards here: https://lnkd.in/eSw3bWTK standards

We’re proud to be part of the Data & Trust Alliance and excited about the new v1.0.0 Data Provenance Standards! 💥(https://vendia.fyi/3zR0Vxb) These standards are a game-changer, boosting transparency in #artificialintelligence and traditional data applications. By clarifying data origins and usage, companies across all industries can build trust and unlock new possibilities. https://vendia.fyi/3zR0Vxb 👈 Learn more about the standards and hear from Tim Wagner and industry experts across AARP American Express Deloitte Howso Humana IBM Kenvue Mastercard Nielsen Nike Pfizer Regions Bank Transcarent UPS Walmart Warby Parker OASIS EDM Council Dun & Bradstreet SDM #dataprovenance #datastandards #datatransparency #dataecosystem

Looking for free, well-documented, visualized #data to guide your planning and to make the case for your services? Check out this resource . . .

Efficient data governance hinges heavily on well-defined data policies and procedures. They include guiding principles, validation rules, workflows, and metrics for monitoring data and policy compliance. They even establish meticulous guidelines for data quality assurance. By offering a clear roadmap for data handling, including data collection, storage, processing, and disposal, these policies and procedures ensure that the data journey aligns seamlessly with analytical goals. Data governance policies and procedures serve as the guardians of data trustworthiness and the consistency of business processes, making them significant cornerstones in the production of reliable analytics. Want to learn more? Click here 👉https://lnkd.in/gZrys97A #datagovernance #customerdata #charity #nonprofit #analytics

Efficient data governance hinges heavily on well-defined data policies and procedures. They include guiding principles, validation rules, workflows, and metrics for monitoring data and policy compliance. They even establish meticulous guidelines for data quality assurance. By offering a clear roadmap for data handling, including data collection, storage, processing, and disposal, these policies and procedures ensure that the data journey aligns seamlessly with analytical goals. Data governance policies and procedures serve as the guardians of data trustworthiness and the consistency of business processes, making them significant cornerstones in the production of reliable analytics. Want to learn more? Click here 👉https://lnkd.in/gMhCNWjk #datagovernance #customerdata #charity #nonprofit #analytics

A consolidated data strategy is essential for harnessing the power of data and the innovations – like generative artificial intelligence – that rely on a steady stream of consistent, accurate information. The roadmap for developing a data strategy and adopting data-driven solutions includes: • Establishing a vision and rationale for what you want to do with your data • Laying out the strategic principles that will form the structure for your data strategy • Assessing the current state of your data and the data management framework surrounding it • Developing a data governance model • Adopting a master data management plan that lays out who’s responsible for certain data streams and how that information is to be shared within and between departments and third parties • Composing a reference architecture to capture the technical aspects of data handling within your organization • Deploying solutions Where is your organization on this roadmap? If you find your data strategy initiative has stalled, OSCRE can help kickstart it with resources like training, webinars and the OSCRE Industry Data Model™. Visit OSCRE.org for more information. #OSCREIndustryDataModel #DataStrategy #RealEstateDataStandards

Looking at the internal data is a necessary reality check that can allow solutions to be crafted and implemented by internal and external Stakeholders.

Absolutely right Colin. More Metrics data covers a really wide of topic areas to complement other information sources.

Why are data journeys important for charities? We use data every day, in both our work and personal life, and the amount of data generated globally each day is staggering, Learn the key stages of a data journey and why it’s important for your charity. 🔗 Read the full article here ⬇️ https://lnkd.in/e4qBUk7Q #CharityDigital #Data #NonProfit

Nonprofits, do you know what data equity looks like for you? Data collection assessment is one of the ways I explore this question with my community. And every opportunity of such an assessment – regardless of org size or mission – brings me to the same lessons about data collection: ● That the data collection process needs clear objectives throughout the lifecycle of collection. Knowing what you want to achieve helps you choose the right methods, tools, and approaches for that data collection. ● That the data quality matters more than quantity. The quality of data is far more critical than the quantity. High-quality data - accurate, complete, and reliable - leads to more trustworthy and actionable insights. It's better to have a smaller set of high-quality data than a large amount of unreliable information. ● That recognizing and minimizing bias is a continuous commitment. Bias in data collection (and analysis) can easily lead to incorrect conclusions. So potential stages of biases in data collection – example, during designing surveys, selecting data sources, or interpreting data – needs to be actively and continually recognized. ● That ethical considerations with data must be the priority for inclusion. Ethical issues, including privacy, consent, and security, must be at the forefront of any data collection effort. Ensuring that data collection methods are ethical not only protects individuals' rights but also enhances the credibility and integrity of the data and the organization collecting it. ● That continuous learning about data needs to become part of the culture. Data collection assessment is one exercise that creates a dialogue about data equity in the organization. It's essential to continually learn from each project, adapting methods and learning around data equity. Have space and time in the coming year to dig deeper into what/how data equity (for example, doing a data collection assessment for inclusion) could look like? Then, add it to your annual goals. And share back what you learn from this experience. In the meantime, here is a link to some resources for you on data equity: https://lnkd.in/gUK-6M_Y #nonprofits #nonprofitleadership #community