Data & Data Culture
Changing Culture Is Central to Changing Business Models
Leaders need to examine their core beliefs if they want to prosper in a COVID-19 world.
Leaders need to examine their core beliefs if they want to prosper in a COVID-19 world.
A Q&A with AWS’s Ishit Vachhrajani on how leaders can generate excitement about and support for AI organization-wide.
Companies need to identify the type of talent they need in order to become data-driven.
Tech leaders should consider data privacy and security issues while also maximizing customer experience.
A new MIT SMR Executive Guide offers managers and decision makers new insights, research, and strategies for leading a data-driven culture.
AI is a powerful tool for innovation when leaders communicate its benefits.
To better align data teams with business operations, a new organizational structure is needed.
Walmart’s Prakhar Mehrotra discusses leading AI teams and workstreams in this episode of the Me, Myself, and AI podcast.
In an era of constant change, data and analytics teams must change rapidly to enable businesses to survive, never mind compete.
Without visual annotations, charts and graphs are missed opportunities to feed your audience insights from your data.
Companies can use an array of tactics to make sure that their data products inspire action — and create value.
Data-driven culture, ethics and compliance standards for pandemic aid, and effective global operations.
Companies need to evolve and shift thinking around what it means to have a data-driven culture.
To drive major change, companies must link data quality and data science within the organization.
A Q&A with AWS’s Rahul Pathak on the advantages of transitioning your company to a data-driven enterprise.
Companies today are swimming in data — but how do we build a data strategy that creates value?
Developing AI-enabled business models, managing corporate social responsibility, and growing digital ecosystems.
Companies and leaders must strive to build business models using three key components for growth.
Big data mining is no longer enough. Data exchanges will shape new economic ecosystems.
Assessments about China’s strengths in AI may be overblown.