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Data Modeling: Techniques, Best Practices, & Why It Matters?

Astera

Data modeling is the process of structuring and organizing data so that it’s readable by machines and actionable for organizations. In this article, we’ll explore the concept of data modeling, including its importance, types , and best practices. What is a Data Model?

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Health Data Management | Challenges and Best Practices

Astera

The healthcare industry has evolved tremendously over the past few decades — with technological innovations facilitating its development. Billion by 2026 , showing the crucial role of health data management in the industry. and administrative data (insurance claims, billing details, etc.) trillion in 2020, making it 19.7

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Self-Service Analytics for Google Cloud, now with Looker and Tableau

Tableau

With no need to move data to in-memory storage, you can connect to and analyze data wherever it lives, taking full advantage of Google Cloud’s computing capacity—and providing an end-to-end analytics solution. We keep innovating together to scale analytics to anyone across your organization. Optimizing cloud spend.

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Data Vault 2.0: What You Need to Know

Astera

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

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Self-Service Analytics for Google Cloud, now with Looker and Tableau

Tableau

With no need to move data to in-memory storage, you can connect to and analyze data wherever it lives, taking full advantage of Google Cloud’s computing capacity—and providing an end-to-end analytics solution. We keep innovating together to scale analytics to anyone across your organization. Optimizing cloud spend.

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Unleashing the Potential of Insurance Data with AI-Powered Extraction 

Astera

In the ever-evolving insurance landscape, organizations must process and analyze vast volumes of data from multiple sources to gain a competitive edge, optimize operations, and improve customer experiences. This data comes in various forms, from policy documents to claim forms and regulatory filings.

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Analyzing Data from Multiple Sources: The Key to More Powerful Insights

Sisense

Since those early days, Measuremen has broadened its data sources. The app not only documents utilization data, but allows users to add subjective inputs such as personal preferences. The value of large, varied data sources is becoming obvious in air travel, too.