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


12 Real-World Solutions for IoT Analytics

Our interviews with a dozen vendors that have a strategic focus on the Internet of Things and the analytics products to support it reveal that IoT analytics is more than a passing fad or the latest buzzword

Embedding and Operationalizing Analytics for Action: Three Important Takeaways

Close to 50 percent of TDWI survey respondents said they embedded models or algorithms into business processes in some way. What can we learn from these respondents?

Operationalizing and Embedding Analytics: 3 Best Practices for Taking Action

What good is analyzing data if you don't take action on it?

The Changing Face of Geospatial Analytics

Why geospatial and IoT are an important part of big data's evolution.

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.

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