Data Management

Digitalization can’t deliver agility or reliability unless you first determine data access, quality, and lineage.

In a virtual work environment, organizations must reassess their cybersecurity risk profile and IT strategy.

A pharmaceutical giant enlists a consultant to help create an industry-leading global compliance system.

MIT SMR summer 2020 highlights leadership and innovation strategies, employee morale, and data sharing.

Big data mining is no longer enough. Data exchanges will shape new economic ecosystems.

Business leaders must rethink data management to succeed with machine learning.

New research shows how AI will drive changes to organizations, IT strategy, and risk management.

Leaders can have more influence if they emphasize the people behind the numbers.

How companies assign responsibility for analytics is a crucial factor in exceeding business goals.

A classic bar, line, or pie chart is often the best choice for communicating information.

Digital transformation empowers smarter KPIs.

Automation can go far beyond cars. Self-driving company capabilities are closer than we realize.

#MITSMRChat participants shared ideas about best practices for organizations implementing AI.

New research by MIT SMR Connections and NETSCOUT reveals IT leaders’ data analytics priorities.

New research by MIT SMR Connections and SAS reveals how organizations build trust in analytics.

AI-powered systems are joining humans in the workforce, with implications for management strategy.

To make AI a strategic differentiator, organizations need to draw from alternative data sets.

Australian social service agencies are taking the lead in using bots to improve services.

Data on its own has value, but insights from that data substantially increase its value.

Burdened by an overabundance of KPIs, the health care sector can look to machine learning to force a focus on the metrics that matter most.