Four Steps to a Successful Text Analytics Workflow - Story
November 17, 2020When it comes to an end-to-end text analytics workflow, what do engineers need to know? There are four main phases in the workflow:
When to use Machine Learning or Deep Learning? - Story
October 15, 2019In both machine learning and deep learning, engineers use software tools to enable computers to identify trends and characteristics in data by learning from an example data set.
The Perplexities of Predictive Maintenance: Generating and Leveraging Failure Data - Story
April 16, 2019We?ll explore one of the most crucial, and frequently missed, components of predictive maintenance: workflow failures and knowing how to predict them.
The Perplexities of Predictive Maintenance: Synthesizing and Sourcing Adequate Amounts of Data - Story
March 19, 2019Here, we'll explore what happens when the challenge lies with the lack of data, the foundation of any predictive maintenance model.
The Perplexities of Predictive Maintenance: Understanding the Anatomy of a Workflow - Story
February 19, 2019We will explore three common obstacles engineers face when implementing predictive maintenance, and ultimately how to best avoid them, beginning with the fundamental lack of knowledge.
Filling the data scientist gap, part 3: Challenges and solutions for the road ahead - Story
May 01, 2018As organizations begin to put data analytics tools in the hands of their domain experts, challenges can arise, including showing the value of data analytics to those who are skeptical.
Filling the data scientist gap, part 2: Diving into data analytics technologies - Story
April 10, 2018A new set of algorithms and infrastructure has emerged that allows businesses to use key data analytics techniques such as big data or machine learning to capitalize on opportunities.
Filling the data scientist gap, part 1: Turning engineers into data scientists - Blog
February 06, 2018There?s a shortage of data scientists and companies are struggling to fill the void ? but they may find success by focusing on candidates with domain expertise.
Domain experts take on data science - Eletter Product
January 04, 2018In 2018, businesses will continue to look to integrate insights derived from big data into their products, services, and operations. However, not all businesses can employ a data scientist.
Smart industry is putting data front and center - Other
July 25, 2016The industrial world is rapidly changing with the emergence of smart industry. Today's production machines and handling equipment have become highly i...