Companies today are drowning in data. The average company exceeds 50 percent per year in volume of data growth and has an average of 33 unique data sources — these are overwhelming amounts that make extracting analytical insights an arduous task. For those swamped with data that’s not being put to use, data lakes can provide immense value. Data lakes are storage systems that hold large volumes of raw, highly diverse data from many sources. Aside from providing internal benefits such as architecture flexibility and scalability, they make processing data quicker and more accurate, uncovering analytical insights that companies didn’t even realize before.
Chief Science Officer Marc Cohen and the data science team at Aktana recently published their research in this area in The Journal of the Pharmaceutical Management Science Association, setting forth a successful machine learning approach for identifying message sequences that maximize open and click-through rates.
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