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RESEARCH & RESOURCES


Featured Webinars

Upcoming Webinars

  • Expert Panel: Real-Time Analytics Use Cases and Architectures

    In this expert panel, TDWI senior research director James Kobielus will discuss the chief enterprise use cases for real-time analytics and the principal architectural considerations for data, analytics, and IT professionals seeking to optimize their infrastructures for these applications. December 9, 2024 Register

International Broadcasts

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

Visual Dashboards for Self-Service BI

A picture can paint a thousand numbers and broaden the appeal of BI tools. A fiercely competitive business environment demands more agility and shorter time to insight. These forces have given rise to visual data discovery tools as a new module in the BI portfolio. Specialty BI vendors are growing rapidly and BI platform vendors have rushed to add visual discovery capabilities to their portfolios.

Cindi Howson


Making Predictive Analytics Consumable

Predictive analytics is a powerful technology that is rapidly becoming mainstream. It is being used across industries to understand and predict customer behavior, detect fraud, determine outcomes, and much more. An important trend in the market is the move to make the output from predictive analytics more consumable by end users.

Fern Halper, Ph.D.


Choosing Data Visualizations to Satisfy User Requirements

Data visualization is hot, but just giving users a library of visual objects will not make them suddenly more productive with data. It is important to match requirements with the right visualization options. Users need data visualization for a variety of business intelligence and analytics activities.

David Stodder


Moving Analytics to the Cloud: Are You Ready?

TDWI has seen a growing interest in utilizing the cloud for deploying reporting platforms, analytic tools, data warehouses, and other databases—and for good reason. The fluid allocation of resources that is typical of a cloud lends itself to analytic projects, especially those utilizing big data. A number of cloud use cases are emerging.

Fern Halper, Ph.D.


Big Data Analytics for Better Customer Intelligence: Steps to Success

Becoming customer centric is a critical success factor for most organizations. The marketplace rewards those that have the smartest and most responsive customer marketing, sales, service, and engagement. Superior use of data is essential to achieving goals in all of these areas. Leading organizations are separating themselves from the pack by deploying big data analytics, data visualization, analytics platforms, and business intelligence to gain the most insight from customer data generated across all channels, including social media.

David Stodder


Modernize Data Warehousing with Hadoop, Data Virtualization, and In-Memory Techniques

A growing number of user organizations are under pressure to capture and manage big data, as well as get business value from big data by analyzing it. To achieve these goals, many organizations are extending and revamping their data warehouse (DW) environments. According to TDWI surveys, the new technologies being adopted most by users who are modernizing their DWs include: Hadoop, Data virtualization, and In-memory techniques.

Philip Russom, Ph.D.


How Data Science Is Changing the Way Companies Do Business

Data scientists are a new type of analyst—part data engineer, part statistician, and part business analyst. And they're in high demand. Companies are combing through résumés and job websites, interviewing recent university grads, and poaching from their competitors in an effort to bring these new talents into their organizations. Of course, we’ve had statistical analysts in our organizations for years. Unfortunately, although these people are great at analyzing data, they are not always the best at explaining their findings to executives and business workers in understandable terms.

Colin White


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