Remove Data Governance Remove Data Modelling Remove Data Quality Remove Data Requirement
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Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

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The Best Fivetran Alternatives in 2024

Astera

So, in case your data requires extensive transformation or cleaning, Fivetran is not the ideal solution. Fivetran might be a viable solution if your data is already in good shape, and you need to leverage the computing power of the destination system. Change data capture (CDC) for all relational databases in one platform.

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What Is Data Management and Why Is It Important?

Astera

Securing Data: Protecting data from unauthorized access or loss is a critical aspect of data management which involves implementing security measures such as encryption, access controls, and regular audits. Organizations must also establish policies and procedures to ensure data quality and compliance.

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Top Data Analytics Terms You Should Know

The BAWorld

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.

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

Astera

Modern data architecture is characterized by flexibility and adaptability, allowing organizations to seamlessly integrate structured and unstructured data, facilitate real-time analytics, and ensure robust data governance and security, fostering data-driven insights.

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The Top 7 Data Aggregation Tools in 2024

Astera

Enterprise-Grade Integration Engine : Offers comprehensive tools for integrating diverse data sources and native connectors for easy mapping. Interactive, Automated Data Preparation : Ensures data quality using data health monitors, interactive grids, and robust quality checks.