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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’s New in Data Vault 2.0? Data Vault 2.0

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Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing

Astera

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing As businesses deal with larger and more diverse volumes of data, managing that data has become increasingly difficult. These examples show the high level of flexibility and adaptability provided by data vault.

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Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

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The Future of AI in Data Warehousing: Trends and Predictions 

Astera

Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information.

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The Benefits of Using a Data Warehouse for Healthcare Data Management

Astera

In the world of medical services, large volumes of healthcare data are generated every day. Currently, around 30% of the world’s data is produced by the healthcare industry and this percentage is expected to reach 35% by 2025. The sheer amount of health-related data presents countless opportunities.

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Patient 360 & Journey Mapping using Graph Technology

GAVS Technology

With rising demands for quality and cost-effective patient care, healthcare providers are focusing on data-driven diagnostics while continuing to utilize their hard-earned human intelligence. In other words, data-driven healthcare is augmenting human intelligence. Srinivasan Sundararajan. 360 Degree View of Patient.

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7 Data Quality Metrics to Assess Your Data Health

Astera

Data that meets the requirements set by the organization is considered high-quality—it serves its intended purpose and helps in informed decision-making. Such a detailed dataset is maintained by trained data quality analysts, which is important for better decision-making and patient care. million annually due to low-quality data.