Astera

NOVEMBER 1, 2023

Introduction   As financial institutions navigate intricate market dynamics and heighten regulatory requirements, the need for reliable and accurate data has never been more pronounced. This has spotlighted data governance—a discipline that shapes how data is managed, protected, and utilized within these institutions.

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Astera

MAY 9, 2023

In such a scenario, it becomes imperative for businesses to follow well-defined guidelines to make sense of the data. That is where data governance and data management come into play. Let’s look at what exactly the two are and what the differences are between data governance vs. data management.

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Astera

MARCH 20, 2024

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?

Data Management 52

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Astera

JANUARY 2, 2024

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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Astera

AUGUST 8, 2023

The drag-and-drop, user-friendly interface allows both technical and non-technical users to leverage Astera solutions to carry out complex data-related tasks in minutes, improving efficiency and performance. 2. Talend Talend is another data quality solution designed to enhance data management processes.

Data Quality 52

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Astera

JULY 13, 2023

Data integration involves combining data from different sources into a single location, while data consolidation is performed to standardize data structure to ensure consistency. Organizations must understand the differences between data integration and consolidation to choose the right approach for their data management needs.

Data Warehouse 40

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Astera

APRIL 24, 2024

The platform leverages a high-performing ETL engine for efficient data movement and transformation, including mapping, cleansing, and enrichment. Key Features: AI-Driven Data Management : Streamlines data extraction, preparation, and data processing through AI and automated workflows.

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