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December 2012: Alation forms and goes to work creating the first enterprise data catalog. Later, in its inaugural report on data catalogs, Forrester Research recognizes that “Alation started the MLDC trend.”. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and DataQuality, 2016 report.
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But in the context of data, we have yet to have a very systematic way of improving the datasets that we have in ML. This plot, which is effectively looking from 2012 to 2021, is showing that we have invested a huge amount of effort in improving the models in the ML context. First is how good is your training data?
But in the context of data, we have yet to have a very systematic way of improving the datasets that we have in ML. This plot, which is effectively looking from 2012 to 2021, is showing that we have invested a huge amount of effort in improving the models in the ML context. First is how good is your training data?
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The benefits of this solution are: You can flexibly achieve data cleaning, sanitizing, and dataquality management in addition to chunking and embedding. You can build and manage an incremental data pipeline to update embeddings on Vectorstore at scale. You can choose a wide variety of embedding models.
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