Remove Data Governance Remove Data Preparation Remove Data Silos
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Solving Complex Telecom Challenges with Data Governance and Location Analytics

Precisely

Read our eBook Data Governance 101 Read this eBook to learn about the challenges associated with data governance and how to operationalize solutions. Read Common Data Challenges in Telecommunications As natural innovators, telecommunications firms have been early adopters of advanced analytics.

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Data Fabric and Address Verification Interface

IBM Data Science in Practice

Insights from data gathered across business units improve business outcomes, but having heterogeneous data from disparate applications and storages makes it difficult for organizations to paint a big picture. How can organizations get a holistic view of data when it’s distributed across data silos?

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Why Is Data Quality Still So Hard to Achieve?

Dataversity

We exist in a diversified era of data tools up and down the stack – from storage to algorithm testing to stunning business insights. appeared first on DATAVERSITY.

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How to Power Successful AI Projects with Trusted Data

Precisely

Without proper data preparation, you risk issues like bias and hallucination, inaccurate predictions, poor model performance, and more. “If If you do not have AI-ready data, then you’re more than likely to experience some of these challenges,” says Cotroneo. AI systems require high-quality, well-governed data to avoid missteps.

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Modern Data Management Essentials: Exploring Data Fabric

Precisely

While data fabric is not a standalone solution, critical capabilities that you can address today to prepare for a data fabric include automated data integration, metadata management, centralized data governance, and self-service access by consumers.

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Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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Data Quality in Machine Learning

Pickl AI

Strategies to Improve Data Quality High-quality data is a strategic asset that fuels innovation, drives informed decision-making, and enhances operational efficiency. Data Governance and Management Effective data governance is the cornerstone of data quality.