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Data Vault vs. Data Mesh: Choosing the Right Data Architecture?

Astera

Data volume continues to soar, growing at an annual rate of 19.2%. A solid data architecture is the key to successfully navigating this data surge, enabling effective data storage, management, and utilization. Think of data architecture as the blueprint for how a hospital manages patient information.

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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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Analyst, Scientist, or Specialist? Choosing Your Data Job Title

Sisense

They then translate those needs into system specifications and look for the most attractive financing options for such systems. This includes database modeling, metrics definition, dashboard design , and creating and publishing executive reports. Database design is often an important part of the business analyst role.

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How to: Focus on three areas for a holistic data governance approach for self-service analytics

Tableau

While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling. Data migration . Data architecture. You may be familiar with our mission at Tableau: to help people see and understand data.

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How to: Focus on three areas for a holistic data governance approach for self-service analytics

Tableau

While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling. Data migration . Data architecture. You may be familiar with our mission at Tableau: to help people see and understand data.

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What Is Embedded Analytics?

Insight Software

Advanced Analytics Provide the unique benefit of advanced (and often proprietary) statistical models in your app. Data Environment First off, the solutions you consider should be compatible with your current data architecture. Look for those that do not require data replication or advanced data modeling.