More organizations and their leaders are looking to Big Data to transform processes and elevate the quality of products and services. Yet, gathering and storing large amounts of data isn't the quick fix often sought after. Without analysts-the human component-to interpret that data, the cost of incorrect or misinterpreted data can greatly impact organizations. In this book, William Mawby examines the claims of Big Data analysis in detail. Using examples to illustrate potential problems that may lead to inefficient and inaccurate results, Mawby helps practitioners avoid potential pitfalls and offers application methods to incorporate Big Data analytics into your company that will enhance your analytic efforts.
Big data analytics is defined as the use of algorithms on large data sets to drive decisions that are of value to a company or Often the power of a big data analytics approach is emphasized by describing it as having three βVβ words: volume, velocity, and variety.
At the leading edge of this push to leverage Big data is the development of the new field of Deep Learning is a direct attempt to replace human cognition with a that usually relies on using a multilayered neural network to mimic the human brainβs complex structure of synaptic connections. Although Deep Learning seems to be making some progress, it is nowhere near its ultimate objective to achieve strong Artificial Intelligence that will replace humans. The dream of Artificial Intelligence seems to be a world in which the human analytics practitioners have nothing to do but slowly sip their lattes while the algorithm solves all of their problems.
William D. Mawby, Ph.D. has extensive consulting, teaching, and project experience and has taught more than 200 courses on many subjects in statistics and mathematics. He is currently writing, teaching courses on climate change and big data, and volunteering at the American Association for the Advancement of Science and the Union of Concerned Scientists.