Precisely

SEPTEMBER 18, 2023

Author’s note: this article about data observability and its role in building trusted data has been adapted from an article originally published in Enterprise Management 360. Is your data ready to use? That’s what makes this a critical element of a robust data integrity strategy. What is Data Observability?

Data Observability 52

Data Observability Data Quality Data Pipeline DataOps 52

IBM Journey to AI blog

OCTOBER 22, 2024

Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI). Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Precisely

AUGUST 29, 2024

Key Takeaways Data quality ensures your data is accurate, complete, reliable, and up to date – powering AI conclusions that reduce costs and increase revenue and compliance. Data observability continuously monitors data pipelines and alerts you to errors and anomalies.

Data Governance 52

Data Governance Data Quality Data Observability AI 52

IBM Journey to AI blog

FEBRUARY 26, 2024

Increased data pipeline observability As discussed above, there are countless threats to your organization’s bottom line. That’s why data pipeline observability is so important. That’s why data pipeline observability is so important.

Data Pipeline 112

Data Pipeline Data Engineering Data Engineering Data Engineering 112

IBM Journey to AI blog

APRIL 10, 2023

A data fabric is an architectural approach designed to simplify data access to facilitate self-service data consumption at scale. Data fabric can help model, integrate and query data sources, build data pipelines, integrate data in near real-time, and run AI-driven applications.

AI 103

AI AI Data Governance Data Pipeline 103

ODSC - Open Data Science

FEBRUARY 14, 2023

Beyond Monitoring: The Rise of Data Observability Shane Murray Field | CTO | Monte Carlo This session addresses the problem of “data downtime” — periods of time when data is partial, erroneous, missing or otherwise inaccurate — and how to eliminate it in your data ecosystem with end-to-end data observability.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

AUGUST 23, 2023

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

Data Governance 66

Data Governance AI AI Artificial Intelligence 66