RESEARCH & RESOURCES

Featured Webinars

  • 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. December 12, 2018 Register

  • 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. December 18, 2018 Register

  • Augmenting BI and Analytics in the Age of AI and Big Data

    Learn about key trends in BI and analytics based on research findings in a just-published TDWI Best Practices Report: "BI and Analytics in the Age of AI and Big Data." We'll cover priorities for augmenting BI, analytics, and data preparation with new AI capabilities, in particular to capture value from big data and cloud data systems. January 16, 2019 Register

Upcoming Webinars

  • 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. December 12, 2018 Register

  • 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. December 18, 2018 Register

  • Augmenting BI and Analytics in the Age of AI and Big Data

    Learn about key trends in BI and analytics based on research findings in a just-published TDWI Best Practices Report: "BI and Analytics in the Age of AI and Big Data." We'll cover priorities for augmenting BI, analytics, and data preparation with new AI capabilities, in particular to capture value from big data and cloud data systems. January 16, 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.


TDWI Membership

Get immediate access to training discounts, video library, BI Teams, Skills, Budget Report, and more

Individual, Student, & Team memberships available.