Data & Data Culture
This Crazy Wave We’re Riding: Walmart’s Prakhar Mehrotra on the Ups and Downs of AI
Walmart’s Prakhar Mehrotra discusses leading AI teams and workstreams in this episode of the Me, Myself, and AI podcast.
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.
Business leaders must rethink data management to succeed with machine learning.
Our experts weigh in on market implications from California’s new consumer privacy act.
Companies already use data to make marketing decisions. Will deep learning enable a leap forward?
A classic bar, line, or pie chart is often the best choice for communicating information.
To avoid bias, people-centered design principles must be the foundation of deep-learning algorithms.
Data and algorithms can mitigate gender bias in venture capital funding.
As AI becomes more ubiquitous, we need clear systems for keeping it in check.