Notes about Cutting-Edge Technologies and Everything

According to Gartner: “By 2022, organizations using multiple go-to-market approaches for digital commerce will outperform noncommerce organizations by 30 percentage points in sales growth." Covid-19 has forced many brands to accelerate their digital-first commerce strategies, sooner than they had planned, in an effort to keep up with customer demands and drive revenue.    Whether your brand was an early adopter, or is still struggling to implement a robust digital commerce strategy, the Gartner Predicts 2021:  COVID-19 Drives Accelerated Shift to Digital and Commerce Model Evolution report will help you prepare for 2021. We believe, in this report you will discover:  5 key digital commerce predictions for 2021 and beyond The market implications of these predictions  How you can embrace new market realities to propel your business Get the report >>>

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The list of linked sources at the end of the article alone is well worth a look. Details: http://bit.ly/2F9kAYe Sources of Market Data on Machine Learning: 2018 Outlook: Machine Learning and Artificial Intelligence , A Survey of 1,600+ Data Professionals.   MEMSQL.   (14 pp., PDF, no opt-in) Advice for applying Machine Learning , Andrew Ng, Stanford University. (30 pp., PDF, no opt-in) An Executive’s Guide to Machine Learning , McKinsey Quarterly. June 2015 An Investors' Guide to Artificial Intelligence , J.P. Morgan. November 27, 2017 (110 pp., PDF, no opt-in) Artificial intelligence and machine learning in financial services Market developments and financial stability implications , Financial Stability Board. (45 pp., PDF, no opt-in) Big Data and AI Strategies Machine Learning and Alternative Data Approach to Investing , J.P. Morgan. (280 pp., PDF. No opt-in). Google & MIT Technology Review study: Machine Learning: The New Proving Ground for Competitive Adva...

The fact that we believe analytics drive performance isn’t enough. This report by David Alles (International Institute for Analytics) provides a range of supporting evidence, using IIA’s proprietary analytics maturity data – from 74 leading companies like Amazon, Apple, Netflix and Google – and publicly available financial and company data, to illustrate the positive association between analytics maturity and superior company performance. Details: http://bit.ly/2tba3u2

CIOs in utilities and other asset-intensive organizations can use this research to support the development of enterprise APM strategies. APM is a key element of the foundational technology that can help their organizations achieve higher levels of operational reliability, safety and efficiency. Key Findings Asset performance management (APM) solutions are widening in scope and decreasing in deployment cost due to market acceptance, increasing competition and maturation of enabling technologies such as advanced analytics, algorithms, cloud and the Internet of Things (IoT). As APM solutions mature and cloud deployment increases, asset management will become a more collaborative process. Activities will be shared among asset owners, operators, service providers and OEMs. Asset management strategies are beginning to shift from preventive to predictive — driven by innovation in enabling technologies and streamlined access to consistent operational technology (OT) data resulting from I...

Details:  https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2018/

In a previous blog we discussed how you enable a highly collaborative and data driven organization through the concepts of multi-speed or bi-modal IT.  We then expanded on this through a discussion on the overall information and analytic lifecycle and the interaction with five persona across that lifecycle. You can read those blogs here:  Multi-speed IT drives fast business experiments and empowered citizen analysts Enabling a highly collaborative and data-driven organization Interestingly enough, Forrester Research recently published a report titled “The False Promise of Bimodal IT” which was referenced in an article on CIO.com . Forrester argues this paradigm is fundamentally a mistake as it creates a two class system with the implication that you have a slow moving entity focused on back office systems (IT) with a second group focused on fast roll out of digital products. From an organizational perspective the arguments being made are valid, but when I th...

Cloud Computing as a term is not very well defined but is often associated with multi-tenant datacentres, commodity computers connected with an IP network, elastic/on-demand resource allocation, and metered billing. Antonio Regalado, a senior editor for biomedicine for MIT Technology Review decided to find out where it all began, https://www.technologyreview.com/s/425970/who-coined-cloud-computing/