Octopai

MAY 2, 2022

A successful data analytics team is one that can increase the quantity of data analytics products they develop in a given time while ensuring (and ideally, improving) the level of data quality. Through jidoka, quality problems are stopped in their tracks and prevented from reaching the consumer. . Enter DataOps.

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

Alation

SEPTEMBER 28, 2022

DataOps is a set of technologies, processes, and best practices that combine a process-focused perspective on data and the automation methods of the Agile software development methodology to improve speed and quality and foster a collaborative culture of rapid, continuous improvement in the data analytics field. Simplicity.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

datapine

JANUARY 31, 2022

The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214