Data is digital transformation’s primary resource. Sufficient investment in infrastructure is necessary to ensure that this resource is first harvested, and then fully utilised.
However, there are three major challenges. The first is the shortage of data scientists — the experts with programming skills, statistics and machine learning knowledge, and an understanding of the business.
Finding these experts is proving challenging and this shortage is stifling machine learning initiatives. The second is time to value: machine learning projects can take weeks or months to deliver the predictions needed for digital transformation. The third is ensuring the quality of the resulting model — vital to guaranteeing the actions taken impact earnings.
DataRobot, the pioneer of machine learning automation, was founded in 2012 to address these challenges. The company hired some of the leading data scientists on the planet – Kaggle competition winners – and set about teaching the machines how to do the job of a data scientist.
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