Tech suppliers and buyers need a better understanding of the scale-out file-based storage market. Explore the future of scale-out NAS with IDC’s Amita Potnis.
Digital content streaming demands have changed, and the infrastructure supporting content workflow must adapt. Explore these changing requirements with IDC’s Amita Potnis.
Artificial intelligence technologies are diverse – and complex. Explore IDC’s advice around customizing your AI infrastructure stack with Sriram Subramanian.
External data is available about a broad variety of data domains and categories. Explore the Data-as-a-service (DaaS) landscape with IDC’s Lynne Schneider.
There is a new generation of data native workers that can help drive better enterprise intelligence. Learn about their characteristics and benefits with IDC.
Learn how Edge computing, AI, and advanced analytics help to uncover details, trends, and correlations.
We’ve discussed the need
to redefine enterprise intelligence and what the future of intelligence
will look like for technology and business leaders, and we know that
organizations are paying attention. In fact, enterprises spent $200 billion on
data, analytics, and AI software, hardware, and services last year. That
doesn’t even include the investment in external data and internal labor costs
to further fuel intelligence initiatives.
What comes to mind when you think of intelligence within your organization? Is it having access to the latest information on key metrics, such as revenue, costs, and profit? Is it a broader view of ‘all information’ you need to make a decision?
IDC has been using the phrase “data intelligence software” to describe a category of capabilities that provide intelligence about data, and the term “data intelligence” has caught on in the industry. But not all definitions of data intelligence are equal. Let’s take a closer look at how IDC defines the term, and some permutations that have emerged.