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The main solutions on the market are decentralized file storage networks (DSFN) like Filecoin and Arweave, and decentralized datawarehouses like Space and Time (SxT). Built to seamlessly integrate with existing enterprise systems, the datawarehouse lets businesses tap into blockchain data while publishing query results back on-chain.
The natural language capabilities allow non-technical users to query data through conversational English rather than complex SQL. The AI and language models must identify the appropriate data sources, generate effective SQL queries, and produce coherent responses with embedded results at scale.
This allows data that exists in cloud object storage to be easily combined with existing datawarehousedata without data movement. The advantage to NPS clients is that they can store infrequently used data in a cost-effective manner without having to move that data into a physical datawarehouse table.
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It wouldn’t be until 2013 that the topic of data lineage would surface again – this time while working on a datawarehouse project. Datawarehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company.
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