RESEARCH & RESOURCES


Upcoming Webinars

International Broadcasts

TDWI On-Demand Webinars on Data Management, Analytics, & AI

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

Real-Time and Big Data Challenge Data Management Best Practices

The incremental movement toward real-time operation is the most influential trend today in data-driven IT disciplines such as business intelligence (BI), data warehousing (DW), and data integration (DI). From a technology viewpoint, collecting, processing, and delivering data is hard enough; doing it in real time requires effort that is downright Herculean. Thanks to the big data phenomenon, the volume of data continues to swell, exacerbating the situation.

Philip Russom, Ph.D.


Big Data is Adding to Data Management Challenges

As the use of big data grows, the need for data management in the new environment will also grow. The combination of new data and new technology requires new data management capabilities and processes in order to realize the promised benefits.

Mark Madsen


Five Hot Trends Impacting Your Decision-Making Environment and What You Need to Worry About

Big data analytics, mobile devices, cloud-based solutions, social media data, and predictive analytics—these are the major trends in today’s decision-making environments. Exciting, yes, but incorporating these trends can also be quite disruptive to traditional architectures and the implementers, analysts, and decision makers themselves.

Claudia Imhoff, Ph.D.


Top Reasons Why You Should Be Considering Advanced Analytics for Your Organization

Advanced analytics is being embraced at an increasing rate by organizations that need to gain actionable insight from their vast amounts of both structured and unstructured information. Although much of the technology that comprises advanced analytics has been around for decades, over the past several years, adoption has increased for a number of reasons.

Fern Halper, Ph.D.


Five Steps for Getting Your BI Dashboard and Self-Service to the Next Level

Dashboard and self-service excellence is essential to gaining full value from investment in business intelligence tools. Dashboards can play a critical role in increasing an organization’s information awareness and improving overall transparency, strategic alignment, accountability, collaboration, and data governance. However, after initial success in deploying their first dashboards, many organizations struggle with how to get them to the next level of maturity. They also face challenges in keeping growing numbers of dashboards well-managed and in sync, especially as users employ more self-service BI tools and seek to interact with dashboards on their mobile devices.

David Stodder


Operationalizing Big Data Analytics: Turn Isolated Analytic Insights into Repeatable BI Solutions That Benefit the Whole Enterprise

In one of the strongest trends today, many user organizations are moving deeper into advanced analytics with big data. That’s because conventional wisdom now tells us that there are leverage-able business insights to be discovered in big data. Many businesses are deploying teams and tools for big data analytics in silos that are disconnected partially or wholly from the rest of their enterprise. Organizations in this situation are not getting full business value from the new insights being discovered because they are rarely shared throughout the company.

Philip Russom, Ph.D.


Real-Time Business Insight from Big Data

For those of us in IT and especially BI, there’s nothing more exciting than seeing practices and technologies come together in a new combination, to support enterprise business in a new way. At the moment, we are seeing such a confluence of practices and technologies for real time, analytics, big data, and in-memory processing. The combination enables more organizations to credibly address time-sensitive business processes that involve big data and benefit from analytics.

Philip Russom, Ph.D.


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