RESEARCH & RESOURCES

Featured Webinars

  • Six Steps for Generating Business Value from Operational IoT Data

    Learn how to accelerate your organization’s ability to realize business value from operational IoT data, plus best practices for reducing data prep, eliminating data latency, and making operational IoT data actionable. We’ll offer tips for balancing data governance, security, and accessibility. February 26, 2019 Register

  • Cloud Data Warehouses: Are They Right for Your Organization?

    Is the cloud right for your organization? Learn about the state of on-premises versus cloud data warehousing and analytics, use cases for each, and the challenges and best practices for moving to the cloud. A demonstration of a cloud-based data warehouse and analytics solution will also be offered. February 28, 2019 Register

  • Modernizing Metadata

    Learn about innovations in metadata tools, including smart tool automation to improve developer productivity (thanks to smart algorithms and AI) and address data lineage as well as new data semantics to enhance business metadata and improve self-service data exploration and analytics. March 7, 2019 Register

Upcoming Webinars

  • Six Steps for Generating Business Value from Operational IoT Data

    Learn how to accelerate your organization’s ability to realize business value from operational IoT data, plus best practices for reducing data prep, eliminating data latency, and making operational IoT data actionable. We’ll offer tips for balancing data governance, security, and accessibility. February 26, 2019 Register

  • Cloud Data Warehouses: Are They Right for Your Organization?

    Is the cloud right for your organization? Learn about the state of on-premises versus cloud data warehousing and analytics, use cases for each, and the challenges and best practices for moving to the cloud. A demonstration of a cloud-based data warehouse and analytics solution will also be offered. February 28, 2019 Register

  • Modernizing Metadata

    Learn about innovations in metadata tools, including smart tool automation to improve developer productivity (thanks to smart algorithms and AI) and address data lineage as well as new data semantics to enhance business metadata and improve self-service data exploration and analytics. March 7, 2019 Register

  • How to Use Data Prep to Accelerate Cloud Data Lake Adoption

    Learn how you can address data prep challenges as you move to the cloud for data management and how you can turn raw, cloud-based source data into output suited for analytics and ML. Explore the tech trends shaping data prep for cloud data lakes and data warehouses. March 12, 2019 Register

  • Smart Data Discovery and Transparency for Complying with CCPA, GDPR, and other Privacy Regulations

    Learn about the challenges of data privacy and protection regulations such as CCPA and GDPR and the steps necessary to comply. We will examine technologies and best practices to improve compliance and govern the range of sensitive data for trusted BI and analytics processes. March 19, 2019 Register

  • Cloud Data Lakes: Enabling New Business Analytics at High Scale and Low Cost

    This webinar will discuss the business benefits of data lakes, the benefits of deploying a data lake in the cloud (and how use cases and technology requirements affect your platform choice), and why substantial data integration is necessary. March 20, 2019 Register

  • Modern Data Analytics in the Cloud: Achieving an End-to-End Strategy

    Learn how your organization can create an end-to-end strategy that aligns analytics in the cloud with data management. We’ll discuss key issues in supporting today’s analytics workloads, including cloud data warehousing, data preparation and transformation, and visual data interactivity. March 21, 2019 Register

  • Building a Modern Operational Data Warehouse: Seven Tips for Success with Hybrid Data

    How do you get full business value from hybrid data with a modern operational data warehouse (ODW)? Learn how an ODW unifies hybrid data from multiple sources to provide analytics insights rapidly and how an ODW incorporates tech innovations such as columnar data and cloud services. March 27, 2019 Register

  • Modern Data Analytics in the Cloud: Achieving an End-to-End Strategy

    Learn how your organization can create an end-to-end strategy that aligns analytics in the cloud with data management. We’ll discuss key issues in supporting today’s analytics workloads, including cloud data warehousing, data preparation and transformation, and visual data interactivity. March 28, 2019 Register

  • Embedded Analytics: Unleashing Insights Everywhere

    Embedded analytics brings the results of analysis to more decision makers quickly, resulting in smarter decisions faster. No wonder it’s a top strategy for 2019. Learn what embedded analytics is, how it makes such a big impact, how it’s used in applications, and the move toward analytics automation. April 2, 2019 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

Evolution of the Data Lake—Implementing Real-Time Change Data in Hadoop

A ten-fold increase in worldwide data by 2025 is one of many predictions about big data. With such growth rates in data, the “data lake” is a very popular concept today. Everybody touts their platform capabilities for the data lake, and it is all about Apache Hadoop. With its proven cost-effective, highly scalable, and reliable means of storing vast data sets on cost-effective commodity hardware regardless of format, it seems to be the ideal analytics repository. However, the power of discovery that comes with the lack of a schema also creates a barrier for integrating well-understood transaction data that is more comfortably stored in a relational database. Rapidly changing data can quickly turn a data lake into a data swamp.

Krish Krishnan


Up to the Minute: The Need for Rapid Adoption of Streaming Data

As Internet of Things (IoT) technologies become more common and web data grows in volume, there is growing evidence that the ability to analyze continuous data is not only valuable but necessary. In fact, those with the ability to capture and analyze massive numbers of independent continuous data streams will have a powerful capability that will help them to power operational intelligence and predictive analytics. A growing number of applications increasingly rely on fast analysis, but tomorrow’s world will be even more dependent on up-to-the-minute consumption of data streams.

David Loshin


Ask the Expert on the Roles and Construct of a Thriving Analytic Team
TDWI Members Only

Most organizations believe they will achieve better analytic results if they populate a deeper bench of experienced data scientists and machine learning practitioners. But this is akin to building a home exclusively with highly skilled framers, brick layers and cabinet makers. You’ll end up with a solid structure and great workmanship, but not a true functional home.

Keith McCormick


Building a Successful Data Lake in the Cloud

Data lakes on Hadoop have come on strong in recent years because they help many types of user organizations – from Internet firms to mainstream industries – capture big data at scale and analyze or otherwise process it for business value.

Philip Russom, Ph.D.


Location, Location, Location: How Geoenrichment Can Improve Business Intelligence and Analytics

Geospatial data is growing in importance for business intelligence as users seek to make sense of diverse data. One element that many types of data have in common is location. Critical attributes of human, machine, and application-generated data become clearer when the source’s location—or movement from one location to another—is known and incorporated into reporting and analysis. Business users can spot trends, patterns, gaps, and other data relationships more clearly if they are able to visually integrate different types of data with maps. If organizations can enrich demographic, behavioral, operational, and other data with location information, they will be on a faster path to generate breakthrough insights and make smarter decisions.

David Stodder


Using Design Thinking to Unleash Creativity in BI and Analytics Development

Design Thinking methods can help organizations overcome the limitations of traditional BI and analytics development. Design Thinking has enabled retail, banking, and other types of firms to revolutionize how they develop products and services to deliver exceptional customer experiences. These methods offer similar potential for unleashing your organization’s creativity in developing applications and services that delight internal users. With organizations under pressure to deliver higher ROI from data—and frustrated by BI and analytics applications and services that don’t meet users’ requirements or realize value from all the data that they have—now is the time to consider new approaches such as Design Thinking.

David Stodder


Location Analytics for Your Data Lake: Driving New Business Insights and Outcomes

Location information has been a growth area in recent years in data management, as user organizations of many sizes and industries have realized how location information can inspire new business insights, practices, and outcomes. In response, many users have reworked older enterprise data environments to enrich the data with more location information. At the same time they have begun capturing data from new sources that include location information, especially from sensors, machines, devices, vehicles, and the Internet of Things (IoT). Much of this new data is being managed in data lakes, which in turn are usually deployed atop Hadoop.

Philip Russom, Ph.D.


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