Leading in the Age of AI: What Every CxO Needs to Know In the AI era, CxOs must embody adaptability, visionary thinking, and ethical leadership, transforming challenges into opportunities for growth.
Want to speed up your digital transformation initiatives? Take a look at your data Digital transformation has taken center stage in many organizations. Need convincing? * IDC predicts that two-thirds of the CEOs of Global 2000 companies will have digital transformation at the center of their corporate strategies by the end of 2017. * Four in 10 IT leaders in the Computerworld 2017 Tech Forecast study
Opportunity Lost: Data Silos Continue to inhibit your Business According to some estimates, data scientists spend as much as 80% of their time getting data in a format that can be used. As a practicing data scientist, I’d say that is a fairly accurate estimate in many organizations. In the more sophisticated organizations that have implemented proper data
You Need a Chief Data Officer. Here’s Why. Big data has moved from buzzword to being a part of everyday life within enterprise organizations. An IDG survey reports that 75% of enterprise organizations have deployed or plan to deploy big data projects. The challenge now is capturing strategic value from that data and delivering high-impact business outcomes. That’
Big Data Roadmap - A roadmap for success with big data I’m regularly asked about how to get started with big data. My response is always the same: I give them my big data roadmap for success. Most organizations want to jump in a do something ‘cool’ with big data. They want to do a project that brings in new
When it comes to big data, think these three words: analyze; contextualize; internalize If you don’t know, I’m a bit of a data nerd. I’ve been writing about big data, data science, machine learning, and other ‘new’ stuff for years. I believe in data science, and I believe in big data. I’m a fan of machine learning (but think
You (probably) don't need Machine Learning Statistically speaking, you and/or your company really don’t need machine learning. By ‘statistically speaking’, I mean that most companies today have no absolutely no need for machine learning (ML). The majority of problems that companies want to throw at machine learning are fairly straightforward problems that can be