Data & Artificial Intelligence Governance
Deploying AI requires careful management to prevent unintentional but significant damage, not only to brand reputation but, more important, to workers, individuals, and society as a whole. AlyData provides a comprehensive set of strategy, planning, and execution services for data governance and responsible AI using proprietary accelerators and frameworks in conjunction with offerings from leading data governance and responsible AI product vendors.
Good governance is based on fairness, accountability, transparency and explainability.
Governing small and big data has taken on greater importance - given the democratization of data and the enforcement of strict regulations. Our clients in the Financial Services and Healthcare industries engage us to provide a Data Governance Strategy, Organization structure, Policies and Procedures, and Best Practices.
AlyData advisors embed with the client staff to assist and train staff to incorporate governance into their daily routine. We also provide training on tools and techniques that users will require.
AI is becoming an essential component of every organization's analytics strategy. However, with such power comes responsibility - to ensure that the AI developers take into account the legal, ethical, societal laws, regulations company policies, and other important factors when developing the models.
Responsible AI is a framework that focuses on ensuring the ethical, transparent and accountable use of AI technologies in a manner consistent with user expectations, organizational values and societal laws and norms.
AlyData's data governance framework has been extended to include AI Governance as well - since they complement each other. This ensures strong governance with clear ethical standards and accountability frameworks that will allow AI to flourish. We focus on 4 areas - Governance, Design (create and implement solutions that comply with ethical AI design standards and make the process transparent), Monitoring (audit the performance of your AI against a set of key metrics. Make sure algorithmic accountability, bias and security metrics are included.) and Re-skilling (democratize the understanding of AI across your organization to break down barriers for individuals impacted by the technology; revisit organizational structures with an AI mindset; recruit and retain the talent for long-term AI impact.).
Our relatively broad definition of data quality includes data completeness, accuracy, consistency, accessibility, and the qualities that are important to the particular business and are ultimately determined by that individual company.
AlyData has delivered data quality solutions and professional services (data quality strategy, data quality lifecycle, data profiling, data remeditation) to clients to enable them to proactively measure and remediate bad data.
Good data matters—not least for compliance and operational excellence. In addition to complying with regulatory obligations, clean data allows an organization to optimize efficiency, offer modern and streamlined customer journeys, anticipate continually evolving customer needs and desires through effective advanced analytics and artificial intelligence (AI), and even create new businesses.
On every data management and governance initiative, data privacy and security are a major focus. Cyber warfare is a reality that every firm has to deal with. Protecting systems and data assets from malicious attacks is a business imperative. Proactive monitoring, remediation of weaknesses and blocking external and inside threats with the latest technology will prevent financial loss, reputational risk exposure and potential legal liability.
AlyData offers a comprehensive set of services to help you protect sensitive data and ensure privacy to address your compliance and business needs. Our data privacy and cyber experts work with the largest and most complex organizations - to train your staff on latest cyber security methods, protect your ecosystem, remediate code to harden it and repel attacks.