Enterprises want more value from their data, but research from Salesforce shows how silos, gaps in strategy and low data trust continue to limit how far AI can scale.

It’s often said that knowledge is power, and that’s never been more true for businesses than in today’s digital age. Technology tools enable businesses to collect a wealth of information from ...

The Libraries provide guidance for writing Data Management (and Sharing) Plans (DMPs or DMSPs), whether they are required as part of a grant proposal or written electively to support effective ...

About 90% of business data is unstructured and often siloed across systems, according to a Box - sponsored IDC white paper.

This guide explores how regulated laboratories can achieve strong data integrity by digitalizing key processes ...

What does a data quality manager do? Your email has been sent A data quality manager is responsible for assessing, managing and maintaining data quality across an organization. This can include ...

This section breaks down different topics required for the planning and preparation of data used in research at Case Western Reserve University. In this phase you should understand the research being ...

Collibra, Oracle, Tableau and Google Cloud Platform are among the best data management software that help businesses efficiently store, organize and analyze data. Data management software, not to be ...

Robotics companies often have to deal with a simple but confounding problem: Robots produce a lot of data. Even a simple robot can easily produce up to a terabyte of data per day, since they ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...

As part of NIH’s long-standing commitment to promote the sharing of scientific data, NIH has issued the Data Management and Sharing (DMS) policy (effective 01/25/2023) to “promote the management and ...

Data lakes have emerged as a pivotal solution for organisations seeking to harness vast, heterogeneous datasets. This strategy involves storing raw data in its native format in a centralised ...