Systems | Development | Analytics | API | Testing

The Data Challenge Nobody's Talking About: An Interview from CDAO UK

Chief Data & Analytics Officer UK (CDAO UK) is the United Kingdom’s premier event for senior data and analytics executives. The three-day event, with more than 200 attendees and 50+ industry-leading speakers, was packed with case studies, thought leadership, and practical advice around data culture, data quality and governance, building a data workforce, data strategy, metadata management, AI/MLOps, self-service strategies, and more.

Modern Marketing Data Stack: Best Practices from Analyzing Snowflake's Customer Base

Are you efficiently unifying, modeling, analyzing, and activating all the data you need to drive impactful marketing campaigns and customer experiences? For years, marketing teams have struggled to operate from a single view of the customer and their business, essential to powering personalized experiences and measuring impact on key KPIs such as sales, growth, and profitability. Today, only half of all marketers have a unified view of the customer.

Built with BigQuery: BigQuery ML enables Faraday to make predictions for any US consumer brand

In 2022, digital natives and traditional enterprises find themselves with a better understanding of data warehousing, protection, and governance. But machine learning and the ethical application of artificial intelligence and machine learning (AI/ML) remain open questions, promising to drive better results if only their power can be safely harnessed.

Yellowfin 9.8 Release Highlights

Introduced in 9.7 as the simplest way to ask questions of your data, Yellowfin 9.8 delivers exciting updates to Guided NLQ, and additional improvements to our report builder. The latest release makes Guided NLQ even more powerful and simpler to use, with new question types (Cross-tab), more intuitive questions with field synonyms and default date periods, and protection against long-running queries - in addition to faster report building.

Demo: Unravel Data - Automated Troubleshooting for Job Failures

For DataOps teams, job failures are common. But finding the issue is (traditionally) where things get even worse. It can take hours or days to troubleshoot a job failure. Unravel Data provides a single view where DataOps teams can locate exactly where–and why–a job failed, along with precise recommendations to troubleshoot the error. DataOps teams are now able to both diagnose and troubleshoot job failures in minutes instead of days or weeks.