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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)? Management of all enterprise data, including master data.

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The Best Data Management Tools For Small Businesses

Smart Data Collective

Data management approaches are varied and may be categorised in the following: Cloud data management. The storage and processing of data through a cloud-based system of applications. Master data management. The tool assigns the role of ‘data stewards’ in an organisation to manage master data.

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What is Metadata Management? Benefits, Framework, Tools, Use Cases, Best Practices

Astera

Let’s look at some of the metadata types below: Operational metadata: details how and when data occurs and transforms. This metadata type helps to manage, monitor, and optimize system architecture performance. Examples include time stamps, execution logs, data lineage, and dependency mapping. Image by Astera.

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Top 6 Mulesoft Alternatives & Competitors in 2024

Astera

Mulesoft and Its Key Features MuleSoft provides a unified integration platform for connecting applications, data, and devices on-premises and in the cloud. Built on Java, its Anypoint Platform acts as a comprehensive solution for API management, design, monitoring, and analytics. Key Features: Drag-and-drop user interface.

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Data Quality Framework: What It Is and How to Implement It

Astera

Data cleaning , or cleansing, enables you to detect and fix these inconsistencies in your data sets, making it fit for purpose. Data quality monitoring Data quality monitoring is the ongoing process of measuring and evaluating the quality of your data across various dimensions.

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How Data Management and Big Data Analytics Speed Up Business Growth

BizAcuity

A strong implementation of big data strategy, architecture, governance and management will reduce the risks of prominent challenges to big data analytics. Big Data Storage Optimization. As mentioned, big data storage optimization is a tedious task with a lot of room for security errors if not carefully monitored.

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Unifying Data from Multiple Sources: Data Integration and Data Consolidation in Data Preparation 

Astera

One of the key benefits of a data lake is that it can also store unstructured data, such as social media posts, emails, and documents. This makes it a valuable resource for organizations that need to analyze a wide range of data types.