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Summary: This blog explains how to build efficient datapipelines, detailing each step from data collection to final delivery. Introduction Datapipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.
Implementing a data fabric architecture is the answer. What is a data fabric? Data fabric is defined by IBM as “an architecture that facilitates the end-to-end integration of various datapipelines and cloud environments through the use of intelligent and automated systems.”
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This adaptability allows organizations to align their data integration efforts with distinct operational needs, enabling them to maximize the value of their data across diverse applications and workflows. IBM Databand underpins this set of capabilities with dataobservability for pipeline monitoring and issue remediation.
The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. The most important reason for using DBT in Data Vault 2.0 is its ability to define and use macros.
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