“The ‘Age of Automation’ is upon us. Companies strive to reduce their costs by using technology to replace humans at every opportunity. Business executives fight over experts in artificial intelligence and data science in hopes of attaining a competitive edge over their rivals. Even the wary flock to siren calls of ever-greater efficiency via investments in computers, robotics and software.” Mark Dickson ( 24.08.2017 )

“Machines are for answers; humans are for questions. The world that Google is constructing – a world of cheap and free answers – having answers is not going to be very significant or important. Having a really great question will be where all the value is.” Kevin Kelly

“If you’re not doing some things that are crazy, then you’re doing the wrong things.” Larry Page ( 2013 )

“Moving data doesn’t come for free.” Adrian Colyer ( May 25, 2017 )

“Data science is, at its foundation, centered on the analysis of data. The technical areas of data science are those that need direct study to make data analysis as effective as possible The areas are:
1.Statistical theory,
2.Statistical models,
3.Statistical and machine-learning methods,
4.Visualization methods,
5.Algorithms for statistical, machine-learning, and visualization methods,
6.Computational environments for data analysis: hardware, software, and database management, as well as
7.Live analyses of data where results are judged by the subject-matter findings, not the methodology and systems that are used.
Of course, these areas can be divided into sub-areas, which in turn can have sub-sub-areas, and so forth. Also, research in an area can depend heavily on research in others.” Wen-wen Tung, Ashrith Barthur, Matthew C. Bowers, Yuying Song, John Gerth, William S. Cleveland ( 2018 )

“The problems that can be solved with machine learning are often not solvable by other methods.” Zachary Chase Lipton ( January 2015 )

“Randomness refers to the absence of patterns, order, coherence, and predictability in a system.” Kirk Borne ( January 9, 2015 )

“The strategic goal of a Big Data Strategy is to derive insights and make better data-driven decisions faster than competition.” Mithun Sridharan ( September 4, 2014 )

“Cleaning data sets is a very crucial step in any kind of data mining. However, it is many times more important while dealing with unstructured data sets. Understanding the data and cleaning the data consumes the maximum time of any text mining analysis.” Kunal Jain ( August 28, 2014 )

“The more companies characterized themselves as data-driven, the better they performed on objective measures of financial and operational results.” McAfee, Brynjolfsson