This webinar brings together experts from TDWI, Informatica, and Databricks to address the critical challenge of operationalizing AI at enterprise scale.

As organizations look to utilize AI for true business impact, they are discovering that success depends on having a strong, scalable data foundation. Data quality, accessibility, governance, and ...

The Data Quality Maturity Model can help guide organizations on their data quality journey. It provides a framework for companies to understand where they are, where they’ve been, and where they still ...

Note: TDWI’s editors carefully choose press releases related to the data and analytics industry. We have edited and/or condensed this release to highlight key information but make no claims as to its ...

The "big" in "big data" is a function of the volume, variety, and velocity of the information that constitutes it. If you read a dozen articles on big data, there's a good chance the 3 Vs -- volume, ...

For years, TDWI research has tracked the evolution of data warehouse architectures as well as the emergence of the data lake. The two have recently converged to form a new and richer data architecture ...

Predictive analytics can help companies optimize existing processes, better understand customer behavior, identify unexpected opportunities, and anticipate problems before they happen. Almost all of ...

At TDWI's Executive Summit in San Diego, Mark Madsen posed the provocative question: is there a statistically significant correlation between sales of beer and sales of diapers? Madsen, a research ...

All organizations want accurate data to run their operations. Getting data into a useful format is the focus of significant industry attention, whether that data comes from social media, structured ...

A misdiagnosed patient. A denied mortgage. A fraud alert that locks out a legitimate customer. These aren’t edge cases—they’re recurring failures of systems never meant to make high-stakes decisions ...

Enterprises rely on robust data quality management to address challenges and seize strategic and operational advantages in today’s business environment. Data quality management—often known as ...

It is challenging—yet exciting—to compete, collaborate, innovate, and drive efficient business and IT operations in today’s roller-coaster world of continuous changes. Organizations of all sizes need ...