RESEARCH & RESOURCES

Featured Webinars

  • Enabling Data Science to Be Data Science: Strategies for Increasing Self-Service Data Science

    Data science offers great potential for what it can contribute to business strategy and operations—that is, if data scientists are actually able to do data science rather than spend most of their time on data management and preparation. TDWI finds that most data science projects spend the majority of time on these areas rather than on development of analytics, models, and algorithms. To increase business value, organizations need solutions that will flip this ratio. January 23, 2018 Register

  • Ask the Expert on The UX Guide to Analytics
    TDWI Members Only

    Enterprise analytics spans a wide array of categories but they all have one thing in common, they require human interaction to realize value. However, much of that value is often left on the table. Factors such as user interviews, persona design, stakeholder buy in, wireframing, iteration, adoption and feedback are underutilized and greatly increase the risk of user disengagement and stakeholder frustration. Analytics managers and dashboard creators can miss the opportunity to leverage user motivations to drive success. January 25, 2018 Register

  • Making Predictive Analytics Work – 5 Keys to Successful Model Deployment and Management

    Organizations are excited about predictive analytics and machine learning for a number of reasons. Companies want to better understand customer behavior. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing. February 8, 2018 Register

Upcoming Webinars

  • Enabling Data Science to Be Data Science: Strategies for Increasing Self-Service Data Science

    Data science offers great potential for what it can contribute to business strategy and operations—that is, if data scientists are actually able to do data science rather than spend most of their time on data management and preparation. TDWI finds that most data science projects spend the majority of time on these areas rather than on development of analytics, models, and algorithms. To increase business value, organizations need solutions that will flip this ratio. January 23, 2018 Register

  • Ask the Expert on The UX Guide to Analytics
    TDWI Members Only

    Enterprise analytics spans a wide array of categories but they all have one thing in common, they require human interaction to realize value. However, much of that value is often left on the table. Factors such as user interviews, persona design, stakeholder buy in, wireframing, iteration, adoption and feedback are underutilized and greatly increase the risk of user disengagement and stakeholder frustration. Analytics managers and dashboard creators can miss the opportunity to leverage user motivations to drive success. January 25, 2018 Register

  • Making Predictive Analytics Work – 5 Keys to Successful Model Deployment and Management

    Organizations are excited about predictive analytics and machine learning for a number of reasons. Companies want to better understand customer behavior. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing. February 8, 2018 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

Data Lakes: Purposes, Practices, Patterns, and Platforms

We’re experiencing a time of great change, as data evolves into greater diversity (more data types, sources, schema, and latencies) and as user organizations diversify the ways they use data for business value (via advanced analytics and data integrated across multiple analytic and operational applications). To capture new big data, to scale up burgeoning traditional data, and to leverage both fully, users are modernizing their portfolios of tools, platforms, best practices, and skills.

Philip Russom, Ph.D.


Ask the Expert about Data Warehouse Modernization
TDWI Members Only

Despite their ongoing evolution, data warehouses (DWs) are more relevant than ever, as they support operationalized analytics and wring business value from machine data and other new forms of big data. Hence, it’s important to modernize an existing DW environment, to keep it competitive and aligned with business goals, as well as to grow into new data-driven practices and technologies, while also keeping and improving the old ones.

Philip Russom, Ph.D.


Creating Value with Unified Governance

Certainly, every business leader wants to have trusted, secure, consistent and usable information. But data volumes and systems complexity has been increasing for years and most organizations rarely prioritize data governance, so why care now? We’re at the brink of a perfect storm of unprecedented IT megatrends. The convergence of Cloud, Social, Mobile and Big Data foreshadows the upcoming tsunami of data ripe with potential business value. But it will also make the frustrating complexity of your traditional on-premises transactional data management challenges appear amazingly “manageable” in contrast.

Claudia Imhoff, Ph.D.


Take a Dive into the Data Lake

Many organizations have a serious interest in data lakes, at the moment, because of the business analytics and new data-driven practices that lakes promise. Yet, these organizations still aren’t quite ready to take a dive into a data lake. Whether they are unable to define standard structures, align and maintain business meanings, or create a governance strategy, these companies struggle to anticipate what truly lies beneath the surface of the data lake.

Philip Russom, Ph.D.


Rethinking Enterprise BI in a Self-Service World: Balancing User Freedom with Enterprise IT Responsibilities

Both product and tech leaders have always recognized that business intelligence (BI) is most valuable when it is pervasive, contextual, and actionable. A new generation of solutions -- embedded BI – provides unprecedented power to weave reporting and analytics into the fabric of apps and business processes.

David Stodder


Achieving Integration Agility, Scale, and Simplicity via Cloud-Based Integration Platform-as-a-Service

Many firms have mandates to move to clouds, control IT costs, integrate disparate applications, deliver data-driven solutions faster, and provide integration infrastructure for hybrid data ecosystems.

Philip Russom, Ph.D.


Ask the Expert About Data Science
TDWI Members Only

The data and analytics landscape is changing. Although many organizations are still analyzing structured data from their data warehouse, TDWI research indicates organizations have increasing interest in analyzing disparate kinds of data. This data is often large in volume and can require modernizing data infrastructures and platforms. The industry around big data and data science and the emerging role of the data scientist is one result of this evolution/revolution.

Fern Halper, Ph.D.


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