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RESEARCH & RESOURCES

Featured Webinars

Upcoming Webinars

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

Data Warehouse Modernization and Analytics for the Digital Enterprise

More and more, organizations want to base decisions on facts, have complete views of customers, manage operations by the numbers, predict and plan strategically, and compete on analytics. As a foundation for achieving these goals, organizations need a modern infrastructure for data warehousing and business analytics.

Philip Russom, Ph.D.


Faster BI for the Masses: How Search Can Make Analytics More Accessible

Business intelligence is critical to getting answers from data, but for many users it is also a huge source of frustration. Since its beginning, the mission of BI has been to make it faster and easier to locate the right data, query it, and return meaningful answers for reporting and analysis. Newer data visualization and discovery tools have improved the user experience, and data warehouses and data lakes have added terabytes to the data within reach. Yet, it still can be a slow and difficult process to get to the most relevant data without help from technical experts. Users often have to wait for their answers and unless the technical experts also have a strong understanding of the business, the answers are usually inadequate—and the process starts all over again.

David Stodder


Streaming Analytics for Real-Time Action – Best Practices for Getting Started

More often, organizations are realizing that analyzing data in motion- i.e., data that arrives continuously as a sequence of instances- can provide substantial business value. This data comes from sensors, social media feeds, traffic feeds, and much more. TDWI has seen growing interest in event stream processing as well as the real-time, continuous analysis of streaming data.

Fern Halper, Ph.D., David Loshin


Improving Data Preparation for Business Analytics

Data preparation is a hot topic today because modern technologies and practices are finally giving users and IT an alternative to traditionally slow, manual, and tedious steps for getting data ready for business intelligence (BI) and analytics. Data preparation covers a range of processes that begin during the ingestion of raw, structured, and unstructured data. Processes are then needed to improve data quality and completeness, standardize how it is defined for communities of users and applications, and perform transformation steps to make the data suitable for BI and analytics.

David Stodder


Accelerating Analytic Insights via the Hybrid Cloud

More often, organizations are looking to the cloud for analytics. The cloud can provide flexibility, elasticity, and convenience. Organizations are using the cloud for a range of business use cases from reporting and sandboxes to production and IoT analytics, and much more. Cloud analytic services offerings are evolving too and becoming more popular – especially with business customers. As a Service (aaS) offerings can target specific subject areas such as churn-detection-as-a-service or fraud-detection-as-a-service. These can help to jump start improved business outcomes much faster than in-house efforts.

Fern Halper, Ph.D.


Data Preparation for the Rest of Us!

Data preparation for analytics used to reside solely within the IT teams with savvy technical resources. With businesses leaning towards self-service analytics, business analysts and data scientists need data prepared their way on their schedule, not based on IT availability, to drive business forward. Data preparation does not replace traditional data integration or ETL but is complementary to existing business intelligence solutions and allows the business user to easily access the integrated data and combine it with other sets of data thereby realizing the ROI on your BI and analytics investment beyond what your IT teams can deliver.

Claudia Imhoff, Ph.D.


Agile, Fast, and Flexible: Five BI and Data Management Strategies for Meeting New Business Challenges

A signature quality of leading companies is their ability to generate data-driven insights quickly so that they can proactively shift strategies to take advantage of new opportunities. They use data to learn sooner how customer preferences are changing, how to adjust when markets are shifting, and how they can reduce inefficiencies in operations so that resources are deployed the right way.

David Stodder


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