Data Management

Experts Thomas H. Davenport and Randy Bean discuss AI’s business impact and what leaders need to pay attention to now.

Mathematica CIO Akira Bell discusses the role of the chief information officer and best practices on data governance.

A combination of biology and digital engineering is saving lives via improved disease detection.

This free webinar offers expert insights on effective data-management strategies for AI adoption.

With a modest amount of training, nontechnical employees can automate complex processes.

This Strategy Guide offers expert advice on creating a comprehensive and flexible cloud strategy.

Based on their research, the authors share four key ways companies can advance their strategic data-sharing initiatives.

It’s impossible to abolish AI bias in the data behind artificial intelligence models, but companies can remediate it.

Artificial intelligence is quietly improving the management of data, including its quality and security.

ADP’s Jack Berkowitz explains the benefits of having data strategy, data products, and AI oversight within the CDO role.

Successful cyberattacks often result from isolated decisions made without fully considering the potential consequences.

Data science project failure can often be attributed to poor problem definition, but early intervention can prevent it.

A new article series explores how organizations must manage and monitor technology in new ways to achieve positive ethical outcomes.

Making your organization fit for data, enhancing value with nontraditional stakeholders, and supporting working parents.

New research highlights nine key factors impeding organizations’ ability to advance their data science progress.

To monetize data, companies must first transform it so it can be reused and recombined to create new value.

Organizations should manage data science with an appropriate structure and enterprisewide process.

Crowdsourcing platforms, updating how work gets done in a new normal, and simplifying data migration.

To make data migration more effective, start with a minimum set of viable data, leave out nice-to-have data, and weigh speed vs. quality.

Only a third of data executives feel that their role is “successful and established.”