Precisely

MAY 16, 2024

You need to break down data silos and integrate critical data from all relevant sources into Amazon Web Services (AWS). Fuel your AI applications with trusted data to power reliable results. Here’s a snapshot of how you can address each: A more complete dataset helps you realize the full potential of your AI.

AI 69

AI AI AWS Data Quality 69

IBM Journey to AI blog

JULY 3, 2024

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata. Effective data quality management is crucial to mitigating these risks.

AI 45

AI AI Data Quality Database 45

Precisely

FEBRUARY 2, 2023

This requires access to data from across business systems when they need it. Data silos and slow batch delivery of data will not do. Stale data and inconsistencies can distort the perception of what is really happening in the business leading to uncertainty and delay.

Data Pipeline 52

Data Pipeline Data Silos Database Data Observability 52

Precisely

JULY 18, 2024

Here are four aspects of a data management approach that you should consider to increase the success of an architecture: Break down data silos by automating the integration of essential data – from legacy mainframes and midrange systems, databases, apps, and more – into your logical data warehouse or data lake.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

Precisely

FEBRUARY 9, 2024

They’re where the world’s transactional data originates – and because that essential data can’t remain siloed, organizations are undertaking modernization initiatives to provide access to mainframe data in the cloud. That approach assumes that good data quality will be self-sustaining.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69

Precisely

JULY 15, 2024

Even without a specific architecture in mind, you’re building toward a framework that enables the right person to access the right data at the right time. However, complex architectures and data silos make that difficult. It’s time to rethink how you manage data to democratize it and make it more accessible.

Data Governance 72

Data Governance DataOps Data Silos Data Pipeline 72

Precisely

OCTOBER 12, 2023

Monitoring and improving business quality rules and technical quality rules to define what “good” looks like. Creating data observability routines to inform key users of any changes or exceptions that crop up within the data, enabling a more proactive approach to compliance. Internal controls and fraud detection.

Data Quality 64

Data Quality Data Governance ML ML 64