Cookie policy: This site uses cookies (small files stored on your computer) to simplify and improve your experience of this website. Cookies are small text files stored on the device you are using to access this website. For more information on how we use and manage cookies please take a look at our privacy and cookie policies. Some parts of the site may not work properly if you choose not to accept cookies.

Home > SAS > OReilly: The Evolution of Analytics: Opportunities and Challenges for Machine Learning in Business

OReilly: The Evolution of Analytics: Opportunities and Challenges for Machine Learning in Business

White Paper Published By: SAS
Published:  May 17, 2016
Type:  White Paper
Length:  41 pages

Over the last several decades, organizations have relied heavily on analytics to provide them with competitive advantage and enable them to be more effective. Analytics have become an expected part of the bottom line and no longer provide the advantages that they once did. Organizations are now forced to look deeper into their data to find new and innovative ways to increase efficiency and competitiveness. With recent advances in science and technology, particularly in machine learning, organizations are adopting larger, more comprehensive analytics strategies.

This report provides a guide to some of the opportunities that are
available for using machine learning in business, and how to overcome some of the key challenges of incorporating machine learning into an analytics strategy. We will discuss the momentum of machine learning in the current analytics landscape, the growing number of modern applications for machine learning, as well as the organizational and technological challenges businesses face when adopting machine learning. We will also look at how two specific organizations are exploiting the opportunities and overcoming the challenges of machine learning as they’ve embarked on their own analytic evolution.

Tags : 
oreilly, evolution of analytics, sas, machine learning, analytics landscape, networking, it management