Recent Work: 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.

Research

TDWI Playbook | Strategies and Practices for Responsible AI
Download this TDWI Playbook today to prepare your enterprise for responsible AI. March 27, 2024 Read Now
TDWI Checklist Report | Five Pillars for the Comprehensive Governance of Data and Other Modern Assets
This TDWI Checklist Report examines five important pillars and best practices for the comprehensive governance of modern data- and AI-related assets. March 21, 2024 Read Now
Digital Dialogue | Using AI to Develop and Optimize Pipelines
In a recent webinar, TDWI VP and senior research director, Fern Halper, Ph.D., spoke to Matillion’s VP of products, Gwendal Vaz Nunes, about using AI to help develop pipelines. March 14, 2024 Read Now
Digital Dialogue | Ensuring Excellence in AI: The Critical Role of Data Governance
This recent webinar covered a range of topics including pillars for AI governance, tools to help, and the importance of automation. Download the recap now. January 31, 2024 Read Now

Webinars

The State of Data Quality – Results of the Latest TDWI Maturity Model Assessment
Please join TDWI’s Fern Halper as she presents the results of TDWI’s most recent maturity assessment on the state of data quality in the enterprise and engages invited subject matter experts from Alteryx, Erwin/Quest, Precisely, and SAP in a panel discussion. May 20, 2024 View Now
The State of Data Quality – Results of the Latest TDWI Maturity Model Assessment
Please join TDWI’s Fern Halper as she presents the results of TDWI’s most recent maturity assessment on the state of data quality in the enterprise and engages invited subject matter experts from Alteryx, Erwin/Quest, Precisely, and SAP in a panel discussion. May 20, 2024 View Now
Expert Panel: Putting Generative AI to Work for Your Organization
Join this TDWI expert panel to learn more about putting generative AI to work in your organization. May 13, 2024 View Now
Expert Panel: Putting Generative AI to Work for Your Organization
Join this TDWI expert panel to learn more about putting generative AI to work in your organization. May 13, 2024 View Now

Upside Articles

What’s Ahead for AI In 2024: The Transformative Journey Continues
Organizations increasingly recognize AI’s role in driving decision-making and fostering growth. Here’s what we can expect from AI in 2024. December 21, 2023 Read More
Generative AI and Its Implications for Data and Analytics
Generative artificial intelligence has captured the imaginations of people around the world. Though not entirely new, generative AI is evolving so rapidly that technology professionals need to track its maturation closely to effectively evaluate the associated opportunities and risks. Here are the basics you need to know. August 23, 2023 Read More
Advanced Analytics: A Look Back at 2021 and What's Ahead for 2022
Organizations will improve data literacy and try to address ever-increasing complex environments next year. December 22, 2021 Read More
Unifying DW and DL: 6 Key Questions
Questions our analysts didn't have time to answer in a recent webinar highlight key considerations for moving to a unified data warehouse/data lake. October 6, 2021 Read More
Don’t Forget the Back End of the Machine Learning Process
Not planning for putting models into production can lead to project failure or increase the amount of time needed to deploy a model. December 8, 2020 Read More
Tackling Bias and Explainability in Automated Machine Learning
Automated machine learning is likely to introduce two critical problems. Fortunately, vendors are introducing tools to tackle both of them. August 17, 2020 Read More

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