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RESEARCH & RESOURCES


Featured Webinars

  • How Generative AI and Large Action Models Will Transform the Way We Work

    In this webinar, TDWI senior research director James Kobielus will discuss the business process automation market, how AI is being adopted in this arena, and how generative approaches such as LAMs offer a fresh new paradigm for automating complex processes faster, cheaper, and more scalably than has been possible with traditional approaches. October 9, 2024

  • The State of Data Governance

    In this webinar, TDWI senior research director James Kobielus will discuss key findings from the recently examined data on coherent strategies for data governance. October 14, 2024

  • Unlocking the Power of Generative AI: 5 Essential Steps to Make It Enterprise-Ready

    Join Fern Halper, Ph.D., TDWI VP of research, and Informatica’s GVP of ecosystems and technology, Rik Tamm-Daniels, as they discuss key requirements for transforming generative AI applications into enterprise-grade solutions. October 17, 2024

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

The Doctor Is In: The Role of the Data Scientist for Analyzing Big Data

No profession is getting more attention these days than that of the “data scientist.” Data scientists have made the covers of business magazines and are practically rock stars at online companies such as Google, Facebook, and LinkedIn.

David Stodder


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.


Data Exploration and Discovery: A New Approach to Business Analytics

Big data and advanced analytics extend the traditional BI environment with new analytic solutions that enhance business decision making and operational efficiency. Examples of solutions include support for new analytics-driven operational applications, analytics accelerators, data transformation hubs, and investigative computing platforms.

Colin White


Integrating Hadoop into Business Intelligence and Data Warehousing

TDWI recognizes that Hadoop usage is a minority practice today, but assumes that mainstream usage of Hadoop within business intelligence (BI) and data warehousing (DW) applications will become common across many industries within a few years. This Webinar provides an overview of Hadoop products and best practices in the context of BI/DW applications so that user organizations can prepare to integrate Hadoop into their BI/DW technology stacks and software portfolios successfully.

Philip Russom, Ph.D.


Future Architectures for Business Intelligence

The things we are building now are yesterday’s future. A revolution is coming in the information delivery market and we are poised at the beginning of that change. The overall picture is fuzzy, but we can see the general outlines of the new architecture.

Mark Madsen


Seven Steps for Implementing Data Discovery Tools

Expectations for what business intelligence needs to deliver are changing fast. At one time, BI technology demanded that users overcome steep learning curves, backlogs for applications, delays for batch queries, limited historical data, and static reports. Now users expect more. Tools and technologies are rapidly evolving to satisfy greater demands for ease of use, timely data access, and deeper analytics.

David Stodder


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.


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