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

What’s Ahead in Data Management in 2019?

Data is evolving into larger volumes from new sources in a wide array of structures, containers, and interfaces. An expert panel discusses data management trends, including new data platforms (Hadoop, cloud computing, and columnar databases), cloud data management, advancements in data catalogs and metadata, and data governance and stewardship.

Philip Russom, Ph.D.


Facilitating Analytics in the Cloud

Explore two different aspects of analytics in the cloud: cloud migration challenges and best practices and how Tableau’s visual analytics platform can be integrated with cloud services to provide self-service access to a broad range of reporting and analytics functions.

David Loshin


Squeeze Every Drop of Business Value from Your Data Lake

Data catalogs contribute ease, precision, and productivity of analytics, self-service, and governance to modern data platforms. Learn how a catalog can inventory data in a data lake for self-service data exploration and data-driven operations and help users find the right data quickly.

Philip Russom, Ph.D.


What’s Ahead in Analytics in 2019?

Experts discuss the hottest trends in analytics, including: predictive analytics/machine learning/AI, self-service analytics, robotic process automation, and intelligent and automated analytics.

Fern Halper, Ph.D.


What’s Ahead in Analytics in 2019?

Experts discuss the hottest trends in analytics, including: predictive analytics/machine learning/AI, self-service analytics, robotic process automation, and intelligent and automated analytics.

Fern Halper, Ph.D.


Best Practices for Managing and Monitoring Open Source Predictive Models

Building a predictive analytics/machine-learning model is far earlier than deploying one, which can take six months or more. Learn how to overcome deployment challenges and monitor models in production, the role open source plays, and what technologies can help support deployment of these models.

Fern Halper, Ph.D.


Best Practices for Real-Time Analytics for High Data Volumes

Learn about hybrid transactional/analytical processing, an alternative architecture that can simultaneously balance transactional and analytical processing. We’ll explain how you can reduce traditional (ETL), manage data storage according to usage, and perform in-memory data management.

David Loshin


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