TDWI Upside - Where Data Means Business

Contributor: Fern Halper


Fern Halper is director of TDWI Research for advanced analytics, focusing on predictive analytics, social media analysis, text analytics, cloud computing, and other “big data” analytics approaches. She has more than 20 years of experience in data and business analysis, and has published numerous articles on data mining and information technology.

Halper is co-author of “Dummies” books on cloud computing, hybrid cloud, service-oriented architecture, and service management, and big data. She has been a partner at industry analyst firm Hurwitz & Associates and a lead analyst for AT&T Bell Labs. Her Ph.D. is from Texas A&M University.

  


All articles by Fern Halper


Four Reasons to Analyze Customer Behavior

How enterprises can engage, retain, and strengthen bonds with their customers.

5 Text Analytics Fundamentals You Should Know

Text analytics is becoming more mainstream and interest in it is growing. Here are five basic things about text analytics you need to know now.

The Internet of Everything vs. the Internet of Some Things

The use of devices connected to the Internet is raising business and ethical questions.

4 Changes with Big Data Analytics

Analyzing big data is different from other analytics. Here are four things worth knowing about analytics at scale.

Does Gender Matter in BI Salaries?

Results from TDWI's newest Salary Survey show continued wage disparity by gender.

Overcoming Challenges in Advanced Analytics

How organizations are improving skills, expanding their technical knowledge, and gaining executive support for next-generation analytics.

Telling a Story with Analysis: 3 Visualization Tips for Presenters

These three best practices will help you deliver visualizations that complement your analysis and make the greatest impression on your audience.

Who Should be Building Predictive Models?

With statistical and data mining skills in short supply, are the right people building your models? These three safeguards can help you avoid model-building problems.

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