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

Getting Data In: Answering the Challenge of Growing Sources of BI Data

Data, data everywhere… Today’s BI and analytics implementation experts are faced with increasing volumes and sources of data – on premises and off – new and innovative technologies, more complex data integration and quality issues, and difficulties in maintaining and enhancing these diverse BI architectures.

Claudia Imhoff, Ph.D.


Understanding and Overcoming Challenges in Data Warehouse Modernization

As the rate of data management innovation accelerates, many data warehouse professionals are beginning to identify where gaps in the conventional data warehouse architecture prevent the organization from getting the best advantage from its information assets. Open source platforms, big data systems, and cloud computing all promise to revolutionize the pervasiveness of business intelligence and analytics across the organization. Consequently, many of these professionals are exploring ways to modernize their business intelligence, reporting, and analytics environments.

David Loshin


Ask the Expert on Data Literacy
TDWI Members Only

Businesses of all types and sizes are becoming more and more defined by their data. As this happens, it is equally important to improve the ability of managers, staff and even the general public, to make decisions which are well-informed by an understanding of the data behind their choices. Data literacy is the ability to understand the nature of the data we work with, and the ways in which we can interpret and communicate through our use of this important resource.

Donald Farmer


Relational Database Vendors are Going Big on Big Data

The number of options for storing, manipulating and accessing data have exploded over the last decade. Open source “NoSQL” (not-only SQL) have spread like wildfire among organizations with cutting-edge analytics. They, along with Hadoop, have lowered the cost barrier to powerful, flexible and incredibly scalable implementations of systems that access unstructured, semi-structured and flexibly-structured data in addition to relational data. However, the learning- and investment-curves have been prohibitive for many organizations. It is all too common that a company would like to advance its database and analytics capabilities with non-relational data but they don’t have the time, human resources or budgets to dedicate to spinning-up and learning how to use these new technologies.

Aaron Fuller


Master Data Management – Avoiding the Potholes

Andy Hayler brings his wealth of practical experience of master data management projects to bear in order to explore best practice in MDM. Drawing heavily on practical project experience, supplemented by survey data from customer projects, he explains the most common problems that MDM projects encounter, and how to avoid them.

Andy Hayler


IoT’s Impact on Data Warehousing: Defining IoT in Terms of Its Data Requirements

The Internet of Things (IoT) is a computing paradigm where a widening range of physical devices—including smartphones, vehicles, shipping pallets, kitchen appliances, manufacturing robots, and anything fitted with a sensor—can transmit data about their location, state, activity, and surroundings. Depending on the device type, some may also receive data and instructions that control device behavior.

Philip Russom, Ph.D.


Integration and Governance for Big Data, Data Lakes, and Hadoop. Yes, you can do it.

In this presentation, we discuss the need for creating a managed data environment that supports the needs of all users of analytical data while ensuring the creation of governed, sharable, and portable data integration and governance work products.

Claudia Imhoff, Ph.D.


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