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Large-scale datawarehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities.
Now, instead of making a direct call to the underlying database to retrieve information, a report must query a so-called “data entity” instead. Each data entity provides an abstract representation of businessobjects within the database, such as, customers, general ledger accounts, or purchase orders. Data Lakes.
This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. Data lakes are more focused around storing and maintaining all the data in an organization in one place.
Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.
Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.
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