InformationWeek: Connecting the Business Technology Community
Updated: 21 hours 15 min ago
The crux of the problem in deploying a data science team is aligning the technical knowledge of a team to the needs of the business and choosing an alignment that offers the greatest impact.
Not all organizations are succeeding with their digital transformation efforts. For one thing, the focus of their success metrics may be too narrow.
Industry leaders scheduled to speak at Interop share their thoughts on key IT trends, challenges and opportunities
Having 200GB speeds in the palm of your hand is going to be a boon for business owners, remote workers, and everyone else who enjoys the internet.
The ongoing buzz surrounding AI and machine learning is a source of optimism, but also raises some concerns.
Data hunter, data scout, or data acquisition specialist may be the new hot career as organizations look to enrich the value of their data analytics and machine learning initiatives with external data.
There is a clear fork in the road, and companies are having to decide which route to take when it comes to open source.
Digital transformation isn't about making incremental improvements on the status quo but using emerging technology to be a leader.
While AutoML might not turn a newcomer into a virtuoso, it does lower the barrier to entry for more businesses to reap the benefits of the data age.
Implementing industrial IoT means adding new types of data and gaining a host of new and unexpected insights.
Applying legacy software development approaches to IoT projects is inefficient and counterproductive. For a growing number of organizations, Agile is the answer.
To liberate the full potential of machine learning as fast as possible, CIOs, CEOs, and society in general, must first get over fears of losing control.
Preparing for his trip to Interop in Las Vegas, an InterOptic exec shares his recommendations for sessions to attend.