Before companies can profit from big data, they often must deal with bad data. There may indeed be gold in the mountains of information that firms collect today, but there also are stores of contaminated or “noisy” data. In large organizations, especially financial institutions, data often suffer from mislabeling, omissions, and other inaccuracies. In firms
Machine learning technology, which is defined in this ProgrammableWeb article, is starting to become a common component in many types of technology platforms. Machine learning has led to the advent of predictive analytics, which has been rapidly...
It’s not every day that Brady gets sent packing, Manning sends potential travelers scrambling to the midwest and a Stanford grad makes news for freaking out on reporter Erin Andrews but that’s exactly what happened on Sunday....
The majority of consumer packaged goods (CPG) companies are failing to place analytics at the heart of their decision-making process, limiting their ability to improve the customer experience and gain business advantage, a study by Accenture has...
Too many people confuse reporting with analytics–and underinvest in making sure they are asking the right questions. Standard-issue reports about monthly employee turnover rates and average compensation per employee are important glances in the rearview mirror. But...
Surprisingly, latest KDnuggets Poll did not find a significant change in Text Analytics use over the past 2 years. While 66% make some use of text analytics, only 19% use it on the majority of their projects....
Building a data science team is difficult enough, but growing one without losing the team’s effectiveness is a major challenge. Here’s why overspecialization is the wrong approach to growth. You’ve built a great data science team,...
Editor’s note: This article compares measures for model performance. Note that “accuracy” is a specific such measure, but that this article uses the word “accuracy” to generically refer to measures in general. In data mining, data scientists...
With the field of predictive analytics becoming a more mainstream business discipline, the end objective for many organizations is to operationalize this discipline in order to truly leverage the full business impact. The notion of “operationalizing” this...
