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RESEARCH & RESOURCES

Featured Webinars

  • Build Data-Intensive Applications Using Cloud Data Platforms

    Does your data platform have the scale, efficiency, and flexibility to meet growing data and analytics needs? Join this TDWI Webinar to learn how developers, ISVs, and SaaS providers can use modern, cloud-based data platforms to meet today’s demand for data-rich applications and SaaS. January 21, 2020 Register

  • Solving Modern Data Integration Challenges with an Enterprise Integration Fabric

    Learn how traditional data integration can impede modern analytics. Explore new ideas for modernizing data integration with enterprise integration fabrics, assessing the scope of enterprise data integration, categorizing access use cases, and integrating new techniques for ETL and change data capture. January 22, 2020 Register

  • Modernizing Data Integration for Cloud Data Warehouses and Lakes

    Compare data integration with cloud versus on-premises systems, learn new capabilities of vendor-built or open-source data integration tools (pipelining, orchestration, and transformation), and explore real-world use cases for modern data integration in data warehousing and analytics. January 28, 2020 Register

Upcoming Webinars

  • Build Data-Intensive Applications Using Cloud Data Platforms

    Does your data platform have the scale, efficiency, and flexibility to meet growing data and analytics needs? Join this TDWI Webinar to learn how developers, ISVs, and SaaS providers can use modern, cloud-based data platforms to meet today’s demand for data-rich applications and SaaS. January 21, 2020 Register

  • Modern Data Sharing for Better Analytics

    Like most practices in data management and analytics, data sharing technology is being used to satisfy new business requirements for collaboration, data science, analytics, data monetization, and sales and marketing. This webinar explores trends and innovations in data sharing. January 21, 2020 Register

  • Solving Modern Data Integration Challenges with an Enterprise Integration Fabric

    Learn how traditional data integration can impede modern analytics. Explore new ideas for modernizing data integration with enterprise integration fabrics, assessing the scope of enterprise data integration, categorizing access use cases, and integrating new techniques for ETL and change data capture. January 22, 2020 Register

  • Modernizing Data Integration for Cloud Data Warehouses and Lakes

    Compare data integration with cloud versus on-premises systems, learn new capabilities of vendor-built or open-source data integration tools (pipelining, orchestration, and transformation), and explore real-world use cases for modern data integration in data warehousing and analytics. January 28, 2020 Register

  • The Automated Business Glossary: Part and Parcel of BI Intelligence

    Learn what a business glossary is and why it is needed, how it tames BI chaos, why it must be part of the BI suite, three tech components that should be automated for a mature and trusted glossary, and how to get started creating an automated business glossary for your organization. February 4, 2020 Register

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

Automation First as a Strategy for Data Warehouse Modernization: Achieving Productivity and Flexibility via Modern Tools and Methods

Data warehouse automation tools enable enterprises to work more productively and flexibly. Learn what data warehouse automation is and does, how such efforts work together, and how an “automation first” strategy enables you to achieve development and operations -- not just platform -- goals.

Philip Russom, Ph.D.


The Modernization of the Data Warehouse: Tackling New Architectures for New Use Cases in Analysis and Operations

Business innovation requires bigger and better data which is driving the need to update legacy warehouse designs. We’ll explore critical success factors in DW modernization, including drivers and use cases, new platforms for data management, and the role of cloud, multicloud, and hybrid cloud environments.

Philip Russom, Ph.D.


Modernizing the Logical Data Warehouse

This webinar will explore what a logical data warehouse is and does, the role hybrid data architectures play, and why you need to upgrade the logical, virtual, semantic, and service layers of your DW architecture to support today’s multicloud, hybrid environments.

Philip Russom, Ph.D.


Reducing Analytics Cycle Time with DataOps

Speakers from Forrester, TDWI, and Attunity will introduce the powerful new discipline of DataOps and explain how it brings people, processes, and technology together to accelerate data pipelines for modern data-driven initiatives. They’ll also discuss use cases for DataOps in your organization.

David Stodder


Customer Intelligence in the Age of Consent: How Organizations can Build on Trust to Learn from and Engage with Customers

To be competitive, organizations need to analyze data to better understand their customers -- but they also need customers’ consent as governments institute strict privacy laws that impact analytics and governance. Learn how to create a strategy that balances these competing requirements.

David Stodder


Maximizing the Power of Data with Embedded Analytics

Discover the latest technology trends and practices for embedding robust analytics, data interaction, and content within cloud-based applications and services. Speakers will discuss organizational and project perspectives key to successful embedded analytics for both internal and external users.

David Stodder


Putting the Intelligence in Your Company’s Approach to Artificial Intelligence: It Starts with the Data

TDWI’s VP of Research joins industry thought leaders from Pitney Bowes and Pegasus Knowledge Solutions to discuss actionable insight and best practices you can use to deliver on the AI promise. Learn how AI can help your organization meet data quality goals of reasonableness, consistency, timeliness, and relevancy.

Fern Halper, Ph.D.


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