In most companies, there isn't a Data Science platform for creating experiments that follows a methodology and ensures quality, uniformity, governance, and parameters.
An important key factor for many companies is time to market and competitiveness. While some are struggling to scale and get successful Machine Learning Models into production with a traditional R&D approach, other companies are rapidly turning to off-the-shelf, out-of-the-box platforms to accelerate time to market, reduce operational costs, and increase the success rate.
Either way, having professionals with the appropriate training - both technically and with the business vision - in the development and implementation of Advanced Analytics solutions will significantly increase the chances of success.
The following are the key roles in Advanced Analytics projects.
Synergy and collaboration between these different areas are key to achieve optimal implementation of the strategies.
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