Precisely

SEPTEMBER 9, 2024

Key Takeaways: • Implement effective data quality management (DQM) to support the data accuracy, trustworthiness, and reliability you need for stronger analytics and decision-making. Embrace automation to streamline data quality processes like profiling and standardization. What is Data Quality Management (DQM)?

Data Quality 64

Data Quality Data Profiling Data Lakes Analytics 64

Data Science Dojo

OCTOBER 10, 2023

IMPACT 2023- The Data Observability Summit (Virtual event – November 8) Focus on Data and AI : The summit will illuminate how contemporary technical teams are crafting impactful and performant data and AI products that businesses can rely on. Over 10,000 people from all over the world attended the event.

AI 243

AI AI Data Observability Artificial Intelligence 243

IBM Journey to AI blog

SEPTEMBER 2, 2024

Data engineers often missed subtle signs such as frequent, unexplained data spikes, gradual performance degradation or inconsistent data quality. Better data observability unveils the bigger picture. Until recently, there were few dedicated data observability tools available.

Data Observability 52

Data Observability Data Pipeline Data Engineering Data Engineering 52

Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Plan for data quality and governance of AI models from day one.

Analytics 72

Analytics Analytics Data Governance Data Quality 72

Precisely

FEBRUARY 9, 2024

In 2023, organizations dealt with more data than ever and witnessed a surge in demand for artificial intelligence use cases – particularly driven by generative AI. They relied on their data as a critical factor to guide their businesses to agility and success.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69

Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Plan for data quality and governance of AI models from day one.

Analytics 59

Analytics Analytics Data Governance Data Quality 59

IBM Data Science in Practice

NOVEMBER 28, 2022

IBM Multicloud Data Integration helps organizations connect data from disparate sources, build data pipelines, remediate data issues, enrich data, and deliver integrated data to multicloud platforms where it can easily accessed by data consumers or built into a data product.

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130