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Automate external data discovery and enrichment for more accurate predictive models.
It’s no secret that external data can transform organizations’ data science and advanced analytics, but finding it is easier said than done. Even though there are thousands of data sources available, finding the right one and acquiring it can be a complex, resource-intensive process. It becomes even worse when you do it at scale.
So how can you ensure that you always have access to exactly the data you need? By building a data acquisition strategy that lets you find what you need, on demand. Having the right processes and infrastructure in place can radically change how you find and deploy external data.
This whitepaper discusses:
Automate external data discovery and enrichment for more accurate predictive models.
It's time to take feature generation - a subset of feature engineering - from an art to a science by opening up additional data sources to achieve breakthroughs in predictive models.
This complete guide breaks down data acquisition into six steps, including data provider due diligence and data provider tests to uplift your model's accuracy.
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