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And by leveraging distributed storage and open-source technologies, they offer a cost-effective solution for handling large data volumes. In other words, the data is stored in its raw, unprocessed form, and the structure is imposed when a user or an application queries the data for analysis or processing.
And by leveraging distributed storage and open-source technologies, they offer a cost-effective solution for handling large data volumes. In other words, the data is stored in its raw, unprocessed form, and the structure is imposed when a user or an application queries the data for analysis or processing.
And by leveraging distributed storage and open-source technologies, they offer a cost-effective solution for handling large data volumes. In other words, the data is stored in its raw, unprocessed form, and the structure is imposed when a user or an application queries the data for analysis or processing.
By providing these diverse tools and capabilities, the consumption layer ensures that all users—from data scientists to business analysts—can derive actionable insights and drive informed decision-making across the organization. Schedule a demo today to discover how Striim can transform your data management strategy.
A few tips for a safe migration using data lineage: Document current dataschema and lineage. This will be important for when you have to cross-reference your old data ecosystem with your new one. Analyze your current schema and lineage.
Data Warehouse Security Best Practices Datagovernance is critical to the protection of both internal and customer data. Before you begin any data warehouse migration, take the time to thoroughly review your data security protocols. Send us a note or check out our demo below!
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