The range of technologies and techniques for analyzing vast volumes of data is expanding at a rapid pace. If your organization is looking to leverage data analytics for actionable intelligence, this heat index should be your guide.
Companies are increasingly developing new executive roles aimed at making the organization as a whole more data-driven and digitally adept. Here’s how three new tech exec titles take different approaches to tackling the same problem.
Too often, IT firms are not focused on measuring what actually matters, leading to missed opportunities. Companies need to follow three key steps to hone in on the metrics that sill steer the business to success.
Big data analytics has made such a widespread impact in the agriculture industry that it’s hard to pinpoint all of its effects, and harder still to predict what changes it might bring. These four ways are just a taste of that impact.
Enterprises need to define a path to data-maturity and that requires reshaping and reorganizing their data storage, description, maintenance and value generation processes, procedures, tooling and functions.
As big data analytics continues to transform the economic and social landscape, is it time to ask questions about the ethical nature of the algorithms employed by various organizations? Is it the responsibility of organizations to ensure that their algorithms contribute to social good?
An understanding of coding at its rudimentary level isn’t all about enriching Silicon Valley. It’s about giving our kids the tools to maneuver in the modern world, the building blocks of these otherwise esoteric concepts, and the ability to contribute to what it looks like.
The value of personal data will soon be unlocked for the average user, yet researchers and businesses will also gain greater access. While it’s a bit early to predict exactly how it will look, the function and value of data looks different from just a few years ago – a trend most can agree is welcome.
Artificial intelligence and machine learning can yield game-changing solutions for enterprises. Here’s what senior IT leaders need to know to launch and maintain a successful machine learning strategy.
While BI leverages past and present data to describe the state of your business today, business analytics mines data to predict where your business is heading and prescribe actions to maximize beneficial outcomes.
As digitally native consumers expect higher levels of engagement, insurance companies are identifying new ways to improve customer experience and turning policies for the first time into living, breathing products.
You need to bring together teams from different departments and business lines to develop a more cohesive implementation approach and achieve group consensus. This process is what I refer to as “Data Intelligence” in my book, The Four Intelligences of the Business Mind.
Not every problem can be solved by machine learning, and not every company is poised to apply AI. Here’s how to know whether your IT organization is ready to reap the benefits of artificial intelligence.
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