Data Science refers to the practice of extracting information from existing datasets to identify patterns and predict future outcomes and trends, a key strategy for enterprises that want to develop insights from the massive data volumes held in data warehouses, Apache™ Hadoop® lakes, and spreadsheets.
But, despite the millions of dollars invested in analytics technologies, the majority of companies still struggle to establish an efficient and programmatic way to do analytics at scale. According to Bain & Co., only 4% of enterprises have been able to attribute better decision-making to the use of analytics. Why are these investments failing to meet expectations? In this paper, we delve into today's most common Advanced Analytics myths and offer potential solutions.