“Understanding correlation, multivariate regression and all aspects of massaging data together to look at it from different angles for use in predictive and prescriptive modeling is the backbone knowledge that’s really step one of revealing intelligence…. If you don’t have this, all the data collection and presentation polishing in the world is meaningless.” Mitchell A. Sanders ( August 27, 2013 )

“As organizations adopt machine-learning techniques, they will see immediate competitive advantages in automation, workflow efficiency and human augmentation. Now is the golden time to consider how machine learning could help your organization and implement this science to improve overall efficiency.” Shawn Masters ( April 2, 2015 )

“Business culture needs to go through a fundamental change to become data-driven. It’s not the new tools, more data, or a PhD-holder staff that will make the change happen. A system, a program, or a robot, designed to be most rational, capable, and failure-proof is put to action only if the environment it operates in allows it. Analytics have been available for years, but they continue being misused because the business models they aid are inherently incompatible. Centrally manged organisations by design impede change; its time that decision making becomes more democratic and distributed, as is data.” Eve the Analyst ( 7th November 2017 )

“The human brain is comprised of 300 million pattern matchers fed with data from our five primary senses and memories. In this age of distributed computing and cheap storage in the cloud, “thinking” without a biological brain is possible for the first time in history. The sensory input into this new, extra-corporeal brain is big data.” Daniel Gutierrez ( December 30, 2014 )

“The standard claim is that the observed effect is so large as to obviate the need for having a representative sample. Sorry – the bad news is that a huge effect for a tiny non-random segment of a large population can coexist with no effect for the entire population.” Kaiser Fung

“Interestingly, the number one concern for people in organizations that are just experimenting or planning for big data is the shortage of analytic professionals, which could indicate that organizations yet to take the big data plunge may be held back because of the lack of big data skills available to them.” Lavastorm Analytics ( 2014 )

“Sapientia ex numero. Wisdom from numbers.” Exegetic Analytics

“Analytics is the use of data and related business insights developed through applied analytical disciplines (e.g., statistical, contextual, quantitative, predictive, cognitive and other models) to drive fact-based planning, decisions, execution, management, measurement and learning.” IBM ( March 2011 )

“Startup culture teaches you to be like Steve Jobs, in that you’re right, everyone else is wrong, and your vision will power through.” Eric Jonas

“One clear conclusion of this work is that, although the DL technology has achieved very promising results, there is still a significant need for further research into and development in how to easily and efficiently build high-quality production-ready DL systems. Traditional SE has high-quality tools and practices for reviewing, writing test, and debugging code. However, they are rarely sufficient for building production-ready systems containing DL components. If the SE community, together with the DL community, could make an effort in finding solutions to these challenges, the power of the DL technology could not only be made available to researchers and large technology companies, but also to the vast majority of companies around the world.” Anders Arpteg, Björn Brinne, Luka Crnkovic-Friis, Jan Bosch ( 29 October 2018 )