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

  • Extending Your Data Warehouse Environment with Hadoop: Bringing Enterprise and External Data Together

    Surveys run by TDWI show that roughly a fifth of mature data warehouse environments now include Hadoop in production. Hadoop is becoming entrenched in warehousing because it can improve many components of the data warehouse architecture—from data ingestion to analytics processing to archiving—all at scale with a reasonable price. February 27, 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

What It Takes to Be Data-Driven: Technologies and Practices for Becoming a Smarter Organization

Gut instinct alone is not enough to enable decisions that will drive success. Most businesses today believe in the power of BI and analytics to help drive insight and value. TDWI research indicates that the vast majority of organizations are using technology such as visual analytics and BI dashboards to help them gain insight. However, gaining insight and using that insight to make decisions are often two different things.

Fern Halper, Ph.D., David Stodder


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


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