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RESEARCH & RESOURCES


Featured Webinars

Upcoming Webinars

International Broadcasts

TDWI Webinars on Big Data, Business Intelligence, Data Warehousing & Analytics

TDWI Webinars deliver unbiased information on pertinent issues in the big data, business intelligence, data warehousing, and analytics industry. Each live Webinar is roughly one hour in length and includes an interactive question-and-answer session following the presentation.


On Demand

Big Data and Your Data Warehouse

Just a few years ago, big data was a problem in terms of scaling up IT systems and discovering the business value. Thanks to advances in vendor platforms and user practices, most enterprises today consider big data an opportunity—not a problem—because they can mine and analyze it for valuable business insight.

Philip Russom, Ph.D.


Using Customer Analytics to Make Better Business Decisions

To compete effectively and keep the best customers loyal, organizations need to capture a variety of data about customers and analyze it effectively. This includes tapping new and promising big data sources such as social media data. However, if organizations cannot analyze data in time and deliver insights to business decision makers quickly, all the data in the world won’t make a difference.

David Stodder


Predictive Analytics: A Critical Part of an Evolved Decision Support Platform

Why predictive analytics now? Many companies use BI to get a better understanding of what has already happened in their business—a backward-looking view. Although this can be somewhat useful, organizations can gain real value by harnessing their valuable corporate data to understand why something is happening now, and more important, what's likely to happen next.

Claudia Imhoff, Ph.D.


Critical Success Factors for the Creation of Self-Service BI

Self-service BI is becoming increasingly popular as business users demand more control over their analytical assets and IT continues to be strapped by budget and resource constraints. Many information workers now expect to be able to interact with information and create their own views to address pressing business issues. At the same time, BI teams would like to offload report and analytics creation duties to users and focus on more value-added activities.

Claudia Imhoff, Ph.D.


Improving Ad Hoc Query Speed for Hadoop Data

As user organizations dive deeper into big data analytics, many are depending more heavily than ever on SQL-based, ad hoc queries as their primary method for data exploration and discovery analytics (sometimes called investigative analytics). At the same time, the same organizations are adopting or considering Hadoop as their primary storage platform for big data. SQL-based analytics and Hadoop are good choices in isolation, but bringing them together has a catch: Hadoop’s support for queries is minimal at the moment.

Philip Russom, Ph.D.


Using Analytics to be Predictive and Proactive

Organizations today need to get ahead of events so they can adjust decisions about resources, personnel, up-sell and cross-sell offers, fraud and abuse detection, and more in dynamic fashion. Analytics can play a key role in bringing predictive insights to executives and managers. With these insights coupled with continuous, real-time data views from business and operational intelligence systems, organizations can be “proactive”—that is, they can do more than just react after the fact to events and market changes, and instead shape their own destiny.

David Stodder


Busting 10 Myths about Hadoop

Although Hadoop and related technologies have been with us for several years now, most business intelligence (BI) professionals and their business counterparts still harbor a few misconceptions that need to be corrected about Hadoop and related technologies such as MapReduce.

Philip Russom, Ph.D.


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