Today's selection of cuttings and submissions (updated Thurs Nov 23 2017)
'Data analytics is slowly becoming entrenched in the enterprise. Most organizations are still doing descriptive analytics (historical reporting) and their use of analytics is function-specific. In 2018, more organizations will follow the leaders and increase their levels of sophistication, using predictive and prescriptive analytics to optimize their operations. In addition, more businesses will start interconnecting function-specific analytics to get new insights into customer journeys, risk profiles, and market opportunities'. Read it
A report, Predictions 2018: The Honeymoon For AI Is Over, says enterprises in 2018 will finally move beyond the hype to recognize that AI requires hard work - planning, deploying, and governing it correctly. On the positive side, it sees 'better human and machine collaboration due to improved interfaces; enhancing business intelligence and analytics solutions by moving resources to the cloud; new AI capabilities facilitating the redesign of analytics and data management roles and activities and driving the emergence of the insights-as-a-service market'. Read it
The Competition and Markets Authority is building a new technology team in a bid to keep up with the use of AI, big data and algorithms. The CMA’s new chief executive Andrea Coscelli, said the team would consist of data scientists, computer experts and economists. 'Some companies have a lot of internal knowledge that we don’t necessarily have … and a lot of [technological changes] are happening very fast', added Coscelli. Read it
'How brands can use big data without creeping people out' - a cautionary note from Frances Katz at news publication The Week. 'Having so much information about potential customers at their fingertips may actually be making advertisers lazy... Instead of over-relying on big data, brands should allow it to enhance their advertising, not drive it entirely' (published 13th Nov 2017)
Beyond the Black Box in Analytics and Cognitive - Author and Professor Thomas H Davenport on the need to interpret how *some* AI / machine learning tools arrive at their decisions
Understand the anomalies too - Avi Avital, VP Customer Success at Anodot on 'Business Intelligence 2.0'
ESOMAR Big Data 2016 - a review of the Berlin conference (published Nov 30th 2016)
Harnessing Hindsight - by Bryan Urbick of the Consumer Knowledge Centre.
Drowning in Data - by John Owen of QSR International.
Senior Research Analyst, San Francisco, CA, USA
Lead Data Scientist, Tampa Bay, FL, USA
Research Manager, Quant - Next Generation Digital Agency, Central London
Data Production Technician, London
Statistical Analyst, Bloomfield Hills, MI, USA
Director - Global Data Management Business, Hong Kong
Digital Lead, Canary Wharf, London
Senior Data Scientist, Woking (UK)