Data Mill

Bimodal IT organization

• AI-enabled enterprise starts with education, not tech

  Step one for CIOs charged with building an AI-enabled workplace is to keep up with what's happening in the field. Next is to help their IT teams develop the habit.  Continue Reading

• With AI techniques, don't get stuck in the data quantity rut

  Gartner's Erick Brethenoux gives practical advice on how CIOs can get started with AI. One of his tips: Think data quality, not data quantity.  Continue Reading

• Customer engagement strategies that heed power of social media

  Executives from Legendary Entertainment and Microsoft explain how their customer engagement strategies rely on the power of analytics and a core set of social principles.  Continue Reading

• Microsoft and corporate activism

  Microsoft's chief legal officer talks corporate activism; Legendary Entertainment offers its take on 'Moneyball' for movies: The Data Mill reports from HUBweek.  Continue Reading

• AI models could help companies overcome human bias

  Human bias can be coded into AI models, but can AI models help remove human bias? Two companies make the case.  Continue Reading

• Success with automation and AI requires a high 'RQ'

  CIOs should assess their 'robotics quotient,' a Forrester Research construct that measures how ready organizations are to introduce automation and AI technologies successfully.  Continue Reading

• With artificial intelligence and machine learning, KPIs are crucial

  The CIO of DBS Bank and CTO of Kayak square off at the 2018 MIT Sloan CIO Symposium on how to use AI for business success.  Continue Reading

• With machine learning models, explainability is difficult and elusive

  The enterprise's demand for explainable AI is merited, say experts, but the problem is more complicated than most of us understand and possibly unsolvable.  Continue Reading

• 'Intelligent tutoring systems' use AI to boost student IQ

  Intelligent tutoring systems that track how a student learns become smarter and more useful with practice, according to Carnegie Mellon University's Ken Koedinger. It's all about the data.  Continue Reading

• Gartner's AI 'value chain' offers schema for assessing an AI project

  Analyst Bern Elliot encourages CIOs to approach AI the way a financial advisor approaches an investment portfolio -- with a mix of high-risk and low-risk projects.  Continue Reading

• Digital phenotype introduces new kinds of data to clinical setting

  John Brownstein of Boston Children's Hospital explains how his team is 'putting the public back in public health' by mining troves of nonclinical data culled from social media.  Continue Reading

• Data transparency is the lifeblood of new information economy

  Many companies have invested in the analytics infrastructure that helps turn data into a business asset. Now what? Gartner's Debra Logan offers insight.  Continue Reading

• IoT data analysis may require hybrid approach

  Where should companies analyze their IoT data, and what is AnalyticOps? The Data Mill reports.  Continue Reading

• Pixar president on why building a 'fail fast' culture is hard

  The duality of failure, IBM's bet on cognitive computing, and the difference between a data officer and an analytics officer: The Data Mill reports.  Continue Reading

• The secret to becoming a 'digital master'? Close the IT/business gap.

  Capgemini's Didier Bonnet shines a light on how businesses are mastering the digital transformation: The Data Mill reports from the CDO Summit.  Continue Reading

• Ten analytics success stories in a nutshell

  Analytics success stories from the likes of Burberry, CBS, Coca-Cola and L'Oreal. The Data Mill reports.  Continue Reading

• Seven secrets to big data project success

  Are there traits that spell big data success? Are there big data pitfalls that can spell disaster? The answer is an emphatic “yes,” according to three experts.  Continue Reading

• Does your big data project need a data concierge?

  Big data needs better questions; local data concierges might be the next information governance trend; and the downside of data: The Data Mill reports.  Continue Reading