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TDWI Checklist Report: The Modern Data Warehouse and Analytics Stack

Fern Halper, Ph.D., Vice President and Sr. Director of Research, TDWI
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The Modern Data Warehouse and Analytics Stack

TDWI Checklist: Six Keys for Success

Organizations want flexibility and scalability for their analytics efforts.

TDWI research indicates that companies are typically capturing terabytes of data, from dozens of data sources, with the primary business goal to analyze the data— often in a self-service manner— to drive insight and action. While some organizations are satisfied with the traditional warehouse that deals primarily with structured data and reporting, a rapidly increasing number of organizations recognize the importance of modernizing their warehouse and analytics environment to scale to meet dynamic data and analytics needs. Read this TDWI Checklist Report to learn best practices for the modern data warehouse and modern analytics stack.

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About the author


Fern Halper, Ph.D.

Vice President and Sr. Director of Research, TDWI

Fern Halper, Ph.D., is Vice President and Senior 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, service management, and big data. 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.