Recent Work: Fern Halper

Fern Halper

Fern Halper, Ph.D.

Vice President and Senior Director of TDWI Research for advanced analytics

Fern Halper, Ph.D., is vice president and senior director of TDWI Research for advanced analytics. She is well known in the analytics community, having been published hundreds of times on data mining and information technology over the past 20 years. Halper is also co-author of several Dummies books on cloud computing and big data. She focuses on advanced analytics, including predictive analytics, social media analysis, text analytics, and big data analytics approaches. She has been a partner at industry analyst firm Hurwitz & Associates and a lead analyst for Bell Labs. Her Ph.D. is from Texas A&M University.



  • Making Predictive Analytics Work – 5 Keys to Successful Model Deployment and Management

    Organizations are excited about predictive analytics and machine learning for a number of reasons. Companies want to better understand customer behavior. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing. February 8, 2018 View Now

  • What It Takes to Be Data-Driven: Technologies and Practices for Becoming a Smarter Organization

    Gut instinct alone is not enough to enable decisions that will drive success. Most businesses today believe in the power of BI and analytics to help drive insight and value. TDWI research indicates that the vast majority of organizations are using technology such as visual analytics and BI dashboards to help them gain insight. However, gaining insight and using that insight to make decisions are often two different things. January 10, 2018 View Now

  • Unifying Big Data Workloads in Apache Spark

    Big data can provide a significant path to value for organizations. Organizations are often making use of more advanced analytics against big data as part of this evolution. This includes using machine learning for predictive analytics to better understand and predict customer behavior. It includes analyzing more data in real time to take action on analytics. The use cases are wide and varied. December 13, 2017 View Now

  • Big Data in the Cloud: Strategies for Analytics Success

    Big data is becoming the norm for many organizations, which is a good thing because it can provide a great deal of insight. Big data includes large volumes of disparate data types: structured data as well as “newer” data such as text, images, geospatial and streaming data. Analyzing newer kinds of data is becoming mainstream. November 7, 2017 View Now

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