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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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What is Data Pipeline? A Detailed Explanation

Smart Data Collective

The source from which data enters the pipeline is called upstream while downstream refers to the final destination where the data will go. Data flows down the pipeline just like water. Monitoring. This checks the working of a data pipeline and all its stages. Data Pipeline: Use Cases.

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The 10 Best Airbyte Alternatives In 2024

Astera

The data management and integration world is filled with various software for all types of use cases, team sizes, and budgets. It provides many features for data integration and ETL. Custom Data Transformations: Users can create custom transformations through DBT or SQL. Pros Real-time monitoring and error alerts.

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What Is Data Governance and Why It Matters?

Astera

Implementing security measures to protect data from unauthorized access, breaches, or misuse is crucial for maintaining confidentiality and compliance with regulations. Data Governance Vs. Data Management What’s the difference between data governance and data management?

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What is Data Orchestration? Definition, Process, and Benefits

Astera

One such scenario involves organizational data scattered across multiple storage locations. In such instances, each department’s data often ends up siloed and largely unusable by other teams. This displacement weakens data management and utilization. The solution for this lies in data orchestration.

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As AI Algorithms Become More Sophisticated in Edge Devices, Persistent Data Requirements Must Advance at the Same Pace

Actian

Companies use distributed AI algorithms to monitor and optimize real-time operations – receiving inputs from embedded sensors, GPS-enabled mobile applications, IoT devices, and video cameras and aggregating this data into a holistic, digital representation of the physical operations. How AI at the edge is being used.