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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

  • From Migration to Modernization: Boosting Your Data Infrastructure for Success

    Join this TDWI webinar, with Fern Halper, TDWI’s VP of research; Arnab Sen, VP of data engineering at Tredence; and Sami Akbay, group product manager – data and analytics at Google, to learn how to transition from legacy systems to modern, cloud-based infrastructures, democratize data across the organization, boost operational efficiency, and enable advanced technologies for sustained growth. October 22, 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

Data Exploration and Discovery: A New Approach to Business Analytics

Big data and advanced analytics extend the traditional BI environment with new analytics 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


The Data-Driven CFO: Increasing Finance’s Contribution to the Bottom Line

Today’s CFOs and their IT counterparts are increasingly expected to “do more with less,” providing value-added analytics while maintaining or reducing Finance and IT spend. Analytic improvement is often complicated by the complexity of fragmented financial systems. In response, leading finance departments are increasingly taking a data-driven approach using a common data warehouse and data governance processes to radically simplify their finance architectures.

Fern Halper, Ph.D.


Gathering BI Requirements

Traditional systems development projects are process driven, and the requirements-gathering activities proceed accordingly. Business intelligence initiatives are data driven, and this requires a different approach to understanding the needs. This Webinar examines three major differences and techniques for getting requirements.

Jonathan Geiger


Predictive Analytics in the Cloud: Is It Right for You?

Adoption of predictive analytics has been increasing thanks to a better understanding of the value of the technology, vendors making the technology easier to use, and the availability of computing power. The uses for predictive analytics are extensive and growing. Companies want to understand customer behavior, they want to better predict failures in their equipment, and they want to deploy analytics in order to take action.

Fern Halper, Ph.D.


5 Ways SMBs Are Putting Information to Work

In many ways small and midsize businesses (SMBs) have greater opportunity when using BI. Yes, budgets and resources may be limited, but most SMBs are not as constricted by robust IT infrastructures that control BI access and use like their enterprise counterparts. Consequently, many SMBs are empowered through their BI applications to take advantage of interactive technologies without the limitations of large-scale enterprisewide IT infrastructures.

Lyndsay Wise


Big Data Evolution: The Big Data Platform Grows Up

The big data software ecosystem has evolved into a robust framework for developing analytics applications spanning a wide range of complexity. At the same time, big data deployments more commonly center on the platform as an expansion of the corporate file system. The concept of the data lake resonates with enterprises desiring to offload data assets into a common platform for analysis, yet the analyses often remain batch-oriented—summarizations, aggregations, and other ETL-like tasks.

David Loshin


Developing Better Customer-Facing Analytics

The vast amount of information now available to organizations is spurring a push toward leveraging data to understand customers more completely. Organizations can gain insights from the data they collect, but developing higher retention and better competitive advantage also means providing customers with access to the analytics that apply to them. This is becoming prevalent in vertical markets such as data service providers, education, health care, utilities—the list is endless.

Lyndsay Wise


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