Operationalizing analytics to scale

September 30, 2015
Many companies have invested time and money into building sophisticated data pipelines that can move massive amounts of data, often in real time. However, for the analyst or data scientist who builds offline models, integrating their analyses into these pipelines for operational purposes can pose a challenge. In this slide deck, we will discuss some key technologies and workflows companies can leverage to build end-to-end solutions for automating statistical and machine learning solutions: from collection and storage to analysis and real-time predictions.
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