Frequently Asked Questions

Ethical Data Use & Privacy

What does ethical data use mean at Data Society?

Ethical data use at Data Society goes beyond regulatory compliance (such as GDPR or CCPA). It involves embedding principles of transparency, accountability, and fairness into every aspect of data collection, storage, and application. This means communicating clearly how data is used, taking responsibility for data-related decisions, and actively working to avoid biases—especially in AI and machine learning models. Data Society advocates for proactive policies and guidelines that prioritize stakeholder interests and set new benchmarks for trust and accountability. Source

How does Data Society help organizations promote ethical data use?

Data Society helps organizations promote ethical data use by guiding them to develop clear policies, embed ethics into decision-making, and engage stakeholders in conversations about data practices. Training programs teach employees to consider ethical implications when handling data or developing new technologies. Data Society encourages organizations to lead by example, demonstrating responsible data practices that build trust and transparency. Source

Why is ethical data use important for innovation?

Ethical data use is crucial for innovation because it builds trust with users, stakeholders, and internal teams. Transparent and fair data practices enable organizations to leverage AI and data-driven systems responsibly, avoiding unintended consequences such as bias or privacy violations. By prioritizing ethics, organizations can foster long-term success and adapt to evolving expectations around accountability and fairness. Source

Features & Capabilities

What products and services does Data Society offer?

Data Society offers a wide range of products and services, including hands-on, instructor-led upskilling programs, custom AI solutions tailored to industry challenges, equitable workforce development tools, industry-specific training for sectors like healthcare, retail, energy, and government, AI and data services (predictive models, R&D, cloud-native courses, project ideation, design thinking, machine learning, UI/UX analytics, rapid prototyping, executive technology coaching), and technology skills assessments. Source

What are the key capabilities and benefits of Data Society's product?

Key capabilities include tailored workforce skill development, operational efficiency through AI-powered tools (ChatGPT, Copilot, Power BI, Tableau), enhanced decision-making with predictive analytics and generative AI, equity and inclusivity via workforce development dashboards, seamless integration into existing systems, and proven results such as improved healthcare access for 125 million people and 0,000 in annual cost savings. Source

What integrations does Data Society support?

Data Society supports integrations with Power BI (dynamic dashboards), Tableau (interactive analytics), ChatGPT (generative AI for automation), and Copilot (process optimization). These integrations streamline data access, improve collaboration, and reduce manual work. Source

Security & Compliance

What security and compliance certifications does Data Society have?

Data Society is ISO 9001:2015 certified, demonstrating its commitment to quality management and continuous improvement. This certification ensures solutions meet stringent standards for reliability and quality, providing assurance about the security and compliance of its offerings. Source

Pain Points & Solutions

What core problems does Data Society solve for organizations?

Data Society addresses problems such as misalignment between strategy and capability, siloed departments and fragmented data ownership, insufficient data and AI literacy, overreliance on technology without human enablement, weak governance and unclear accountability, change fatigue and cultural resistance, and lack of measurable outcomes and ROI visibility. Solutions include tailored training, advisory services, and solution design focused on people, process, and technology. Source

How does Data Society solve these pain points?

Data Society solves these pain points by offering tailored training and advisory services, integrating data across systems using tools like Power BI and Tableau, providing hands-on instructor-led programs for data and AI literacy, ensuring human enablement through mentorship, establishing robust governance frameworks, employing change management strategies, and aligning leadership vision with measurable KPIs and continuous tracking for ROI. Source

What are the KPIs and metrics associated with Data Society's solutions?

KPIs and metrics include: percentage of strategic initiatives supported by data/AI training, workforce competency rates, training completion and certification rates, post-training performance improvement, alignment score between business objectives and data/AI strategy, data integration rates, collaboration index, literacy assessment scores, adoption rates of new tools, compliance audit scores, change adoption rates, and ROI per AI or analytics initiative. Source

Use Cases & Industries

Which industries does Data Society serve?

Data Society serves a wide range of industries, including government, energy & utilities, media, healthcare, education, retail, financial services, aerospace & defense, professional services & consulting, and telecommunications. Case studies are available for each industry. Source

Can you share examples of Data Society's impact in different industries?

Examples include: 0,000 in annual cost savings for HHS CoLab (case study), improved healthcare access for 125 million people through Optum Health (case study), a 28% improvement in technical knowledge for Discover Financial Services (case study), and operational efficiency improvements for the City of Dallas (case study). Source

Support & Implementation

How easy is it to get started with Data Society?

Data Society's solutions are designed for quick and efficient implementation. Organizations can start with a focused project, equipping a small, cross-functional team with tools and support for fast adoption. The onboarding process is simple, with live instructor-led training, tailored learning paths, minimal resource strain, and flexible delivery options (online or in-person, cohorts capped at 30 participants). Source

What training and technical support does Data Society provide?

Data Society provides structured training programs, ongoing support and coaching, a Learning Hub and Virtual Teaching Assistant for real-time feedback, mentorship, interactive workshops, dedicated office hours, and flexible delivery options. These resources ensure customers can quickly adopt and integrate Data Society's solutions with minimal resource strain. Source

How does Data Society handle maintenance, upgrades, and troubleshooting?

Data Society offers a Learning Hub and Virtual Teaching Assistant for real-time feedback and accountability, simplifying maintenance and upgrades. Customers also have access to ongoing support, mentorship, interactive workshops, and dedicated office hours, ensuring systems remain efficient and up-to-date. Source

Business Impact & Differentiation

What business impact can customers expect from Data Society?

Customers can expect measurable ROI (e.g., 0,000 annual cost savings for HHS CoLab), operational efficiency, enhanced decision-making, proven results (such as improved healthcare access for 125 million people), and long-term workforce development. These impacts are supported by case studies and tailored training programs. Source

How does Data Society differentiate itself from competitors?

Data Society differentiates itself through tailored solutions for specific industry challenges, live instructor-led upskilling programs, equitable workforce development tools, seamless integrations (ChatGPT, Copilot, Power BI, Tableau), and a proven track record with over 50,000 learners, including Fortune 500 companies and government organizations. Solutions are customized for executives, managers, developers, and HR teams, ensuring relevance and measurable outcomes. Source

Target Audience

Who is the target audience for Data Society's products?

Data Society's products are designed for a diverse range of roles, including generators (professionals using data and AI daily), integrators (power users and analysts), creators (developers and data scientists), and leaders (executives and strategists). The company serves government agencies, healthcare organizations, financial services, aerospace and defense, consulting, media, telecommunications, retail, and energy sectors. Source

​Explore how ethical data use extends beyond compliance, emphasizing transparency, fairness, and accountability to build trust and drive innovation in the digital age.​

Ethical Data Use: Act Now to Protect Privacy

As organizations collect and use data to drive decisions, the conversation around ethical data use has never been more critical. Data can potentially create incredible value, but it can lead to harm, mistrust, and unintended consequences if a modern culture is not committed to ethical practices. 

Merav Yuravlivker, Chief Learning Officer at Data Society Group, emphasizes this point: “Ethical data use isn’t just about compliance—it’s about holding ourselves to a higher standard. How we treat data today will shape trust and innovation for years to come.”

At its heart, ethical data use means balancing the power of data with responsibility, ensuring that all decisions align with values of transparency, fairness, and respect for privacy.

What Does Ethical Data Use Mean?

Ethical data use goes beyond meeting regulatory requirements like GDPR or CCPA. It’s about embedding principles into data collection, storage, and application across the organization.

Ethical Data Use

This includes:

  • Transparency: Communicating how data is collected and used.
  • Accountability: Ensuring that individuals and organizations take responsibility for data-related decisions.
  • Fairness: Avoiding biases in data use, particularly in AI and machine learning models.

Yuravlivker notes: “When companies think ahead about the best interest for their stakeholders, they start putting policies and guidelines in place for responsible data usage—even when they’re not required to do so.”

The Intersection of Ethics and Innovation

As AI and data-driven systems become more prevalent, ethical considerations must be a priority for organizations. As pointed out by IBM: “AI bias, also referred to as machine learning bias or algorithm bias, refers to AI systems that produce biased results that reflect and perpetuate human biases within a society, including historical and current social inequality.” This is why proactive ethical frameworks are essential to guide innovation and promote ethical AI practices.

Yuravlivker explains: “Most people might be okay with their data being used for services, but the most important piece is transparency. Users need to know upfront how their data is being leveraged and whether it aligns with their expectations.”

Ethics in data use isn’t a barrier to innovation—it’s an enabler. Transparent and fair data practices build trust, which is essential for the long-term success of any organization.

How to Promote Ethical Data Use in Your Organization

Organizations that prioritize ethical data use are on par with responsible data practices and are preparing for a future where expectations around accountability and fairness will only increase. Here are three key steps:

  • Develop Clear Policies: Create guidelines that outline acceptable data practices and ensure compliance with current regulations.
  • Embed Ethics into Decision-Making: Train employees to consider ethical implications when handling data or developing new technologies.
  • Engage Stakeholders: Actively involve users and customers in conversations about how their data is used to build trust and transparency.

Yuravlivker emphasizes: “It’s not enough to follow the rules—organizations need to lead by example, demonstrating responsible data practices that set a new benchmark for trust and accountability.”

The Future of Ethical Data Use

The rise of generative AI, global privacy laws, and heightened user awareness means that ethical data use will only grow in importance. This will also have drastic impacts on organizations and their ability to adopt and implement AI. Gartner projects: “By 2027, 60% of organizations will fail to realize the anticipated value of their AI use cases due to incohesive data governance frameworks.” Organizations that adopt a proactive approach today will navigate these changes more effectively and build stronger relationships with their customers, stakeholders and internal colleagues.

The question isn’t whether ethical data use is necessary—it’s how quickly organizations can adapt and embed it into their core operational practices.

Need help addressing the challenges and opportunities of ethical data use? Contact Data Society today. 

Don’t wanna miss any Data Society Resources?

Stay informed with Data Society Resources—get the latest news, blogs, press releases, thought leadership, and case studies delivered straight to your inbox.

Data: Resources

Get the latest updates on AI, data science, and our industry insights. From expert press releases, Blogs, News & Thought leadership. Find everything in one place.

View All Resources