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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

Consider using data catalogs for this purpose. Clean data to ensure data quality. Correct any data quality issues to make the data most applicable to your task. This includes removing invalid or meaningless entries, adjusting data fields to accommodate multiple values, fixing inconsistencies, etc.

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Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

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Crafting a Knowledge Graph: The Semantic Data Modeling Way

Ontotext

Clean your data to ensure data quality. Correct any data quality issues to make the data most applicable to your task. This includes removing invalid or meaningless entries, adjusting data fields to accommodate multiple values, fixing inconsistencies, etc. Maximize the usability of your data.

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The Importance of the Semantic Knowledge Graph

Ontotext

While a knowledge graph can exist without an ontology, an ontology is often represented in a knowledge graph because of the natural human desire to organize data—visually or in structure. Unlock the full potential of your data!