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Enterprise Data Management: Strategy, Benefits, Best Practices

Astera

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Why is Enterprise Data Management Important?

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What Is Data Management and Why Is It Important?

Astera

Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place. But what exactly is data management? What Is Data Management? As businesses evolve, so does their data.

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Now available in Tableau 2021.1—Einstein Discovery in Tableau, quick LODs, a new unified notification experience, and more

Tableau

To learn more, read our updated Tableau Server on Microsoft Azure whitepaper for guidance and best practices. Better manage your data with Tableau Catalog improvements. First, we’ve added automated data quality warnings (DQW) , which are automatically created when an extract refresh or Tableau Prep flow run fails.

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SQL Server for Data Warehouse: Optimizing Data Management and Analysis

Astera

Cut Down Data Warehouse Development Time by up to 80% Traditional data warehouse development requires significant investment in terms of time and resources. However, with Astera DW Builder, you can reduce the entire data warehouse design and development lifecycle by up to 80%. Learn more in this whitepaper.

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SQL Server for Data Warehouse: Optimizing Data Management and Analysis

Astera

Cut Down Data Warehouse Development Time by up to 80% Traditional data warehouse development requires significant investment in terms of time and resources. However, with Astera DW Builder, you can reduce the entire data warehouse design and development lifecycle by up to 80%. Learn more in this whitepaper.

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Data Profiling: Types, Techniques and Best Practices

Astera

Clean and accurate data is the foundation of an organization’s decision-making processes. However, studies reveal that only 3% of the data in an organization meets basic data quality standards, making it necessary to prepare data effectively before analysis. This is where data profiling comes into play.

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Now available in Tableau 2021.1—Einstein Discovery in Tableau, quick LODs, a new unified notification experience, and more

Tableau

To learn more, read our updated Tableau Server on Microsoft Azure whitepaper for guidance and best practices. Better manage your data with Tableau Catalog improvements. First, we’ve added automated data quality warnings (DQW) , which are automatically created when an extract refresh or Tableau Prep flow run fails.