Integrating enterprise data and AI platforms enables organizations to build and deploy more innovative and intelligent applications more rapidly. It lets them build more sophisticated AI applications, ...

TDWI's Best Practices Awards program is designed to identify and honor companies that have demonstrated excellence in developing, deploying and maintaining BI, DW, and applications. The best practice ...

Data science is an interdisciplinary field that combines social sciences, advanced statistics, and computer engineering skills to acquire, store, organize, and analyze information across a variety of ...

Organizations are increasingly turning to data-driven decision-making, yet data integrity remains a challenge. According to recent TDWI research: Only 50% of organizations trust their data. Despite ...

[NOTE -- My new TDWI report about High-Performance Data Warehousing (HiPer DW) is finished and will be published in October. The report’s Webinar will broadcast on October 9, 2012. In the meantime, ...

Predictive analytics is the umbrella term for analyzing patterns found in data to predict future behavior or results. It includes techniques and algorithms found in statistics, machine learning, ...

At Quicken Loans, we believe that optimal model function is best achieved by supplementing our models and data scientists with an advanced suite of supporting technology. We call this our “model ...

Organizations face growing pressure to optimize workflows, reduce operational costs, and enhance customer experiences. Many business-critical processes—such as prior authorizations, underwriting, and ...

The Modern Data Leader’s Summit program is designed and delivered by the experts at TDWI and the Summit Advisory Board. Attend the entire summit and earn a TDWI Modern Data Leadership Certificate on ...

Data visualization and visual data discovery can enable diverse types of users—from data scientists working with big data to nontechnical business managers and frontline users—to see significant ...

Just a few years ago, big data was a problem in terms of scaling up IT systems and discovering the business value. Thanks to advances in vendor platforms and user practices, most enterprises today ...