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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

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Ontotext’s Semantic Approach Towards LLM, Better Data and Content Management: An Interview with Doug Kimball and Atanas Kiryakov

Ontotext

Master data management (MDM), on the other hand, is focused on ensuring data quality and consistency across different systems and applications. MDM creates a single, verified source of data that can be used throughout an organization, and enforce policies and standards to maintain data quality.

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Ontotext Knowledge Graph Platform: The Modern Way of Building Smart Enterprise Applications

Ontotext

The main market driver generating demand for knowledge graphs is that B2B clients are on the lookout for intelligent knowledge management solutions that work the same way as the solutions Apple, Amazon, Google and Microsoft provide to their B2C users. The third challenge is how to combine data management with analytics.

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What is Data Mapping?

Jet Global

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Consumers have grown more and more immune to ads that aren’t targeted directly at them.

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The Gartner 2022 Leadership Vision for Data and Analytics Leaders Questions and Answers

Andrew White

– We see most, if not all, of data management being augmented with ML. Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration.