Data Architecture Data Management Finance 
Astera
JULY 3, 2024
What is Data Architecture? Data architecture is a structured framework for data assets and outlines how data flows through its IT systems. It provides a foundation for managing data, detailing how it is collected, integrated, transformed, stored, and distributed across various platforms.
Astera
SEPTEMBER 4, 2024
Implementing a modern, integrated data architecture can help you break down data silos, which cause C-suite decision-makers to lose 12 hours a week. Furthermore, more than 60% of organizations agree that data silos represent a significant business challenge. Discuss your data strategy with us. What Is Data Mesh?
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Sisense
SEPTEMBER 3, 2020
They then translate those needs into system specifications and look for the most attractive financing options for such systems. ROI (return on investment) is also a key concern, as business analysts apply their data-related activities to finance, marketing, and risk management, for instance.
Tableau
SEPTEMBER 23, 2021
This also helps IT with impact analysis and change management, to understand who and which assets are affected downstream when changes are made to a table. While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling.
Tableau
SEPTEMBER 23, 2021
This also helps IT with impact analysis and change management, to understand who and which assets are affected downstream when changes are made to a table. While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling.
The BAWorld
SEPTEMBER 18, 2024
Data integration enables the connection of all your data sources, which helps empower more informed business decisions—an important factor in today’s competitive environment. How does data integration work? There exist various forms of data integration, each presenting its distinct advantages and disadvantages.
Astera
NOVEMBER 30, 2023
With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, It supersedes Data Vault 1.0, Data Vault 2.0
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