A method for optimizing crop productivity comprising: accessing crop growth information describing, for each of a plurality of plots of land, 1) characteristics of the plot of land, 2) a type of crop planted on the plot of land, 3) characteristics of farming operations performed for the planted crop, and 4) a corresponding crop productivity; normalizing the crop growth information by formatting similar portions of the crop growth information into a unified format and a unified scale; storing the normalized crop growth information in a columnar database; training a crop prediction engine by applying one or more one machine learning operations to the stored normalized crop growth information, the crop prediction engine mapping, for a particular crop type, a combination of one or more characteristics of the plot of land and characteristics of farming operations performed for the planted crop to an expected corresponding crop productivity; in response to receiving a request from a grower to optimize crop productivity for a first type of crop and a first portion of land on which the first crop is to be planted, the request identifying a first set of farming operations to be performed by the grower: accessing field information describing characteristics of the first portion of land; applying the crop prediction engine to the accessed field information and the first set of farming operations to produce a first expected crop productivity; applying the crop prediction engine to the accessed field information to identify a second set of farming operations that can produce a second expected crop productivity; modifying the first set of farming operations based on the second set of farming operations to produce a modified set of farming operations; and in response to the second expected productivity being greater than the first expected productivity, presenting, within an interface of a device associated with the grower, the modified set of farming operations. accessing crop growth information describing, for each of a plurality of plots of land, 1) characteristics of the plot of land, 2) a type of crop planted on the plot of land, 3) characteristics of farming operations performed for the planted crop, and 4) a corresponding crop productivity; normalizing the crop growth information by formatting similar portions of the crop growth information into a unified format and a unified scale; storing the normalized crop growth information in a columnar database; training a crop prediction engine by applying one or more one machine learning operations to the stored normalized crop growth information, the crop prediction engine mapping, for a particular crop type, a combination of one or more characteristics of the plot of land and characteristics of farming operations performed for the planted crop to an expected corresponding crop productivity; in response to receiving a request from a grower to optimize crop productivity for a first type of crop and a first portion of land on which the first crop is to be planted, the request identifying a first set of farming operations to be performed by the grower: accessing field information describing characteristics of the first portion of land; applying the crop prediction engine to the accessed field information and the first set of farming operations to produce a first expected crop productivity; applying the crop prediction engine to the accessed field information to identify a second set of farming operations that can produce a second expected crop productivity; modifying the first set of farming operations based on the second set of farming operations to produce a modified set of farming operations; and in response to the second expected productivity being greater than the first expected productivity, presenting, within an interface of a device associated with the grower, the modified set of farming operations. accessing field information describing characteristics of the first portion of land; applying the crop prediction engine to the accessed field information and the first set of farming operations to produce a first expected crop productivity; applying the crop prediction engine to the accessed field information to identify a second set of farming operations that can produce a second expected crop productivity; modifying the first set of farming operations based on the second set of farming operations to produce a modified set of farming operations; and in response to the second expected productivity being greater than the first expected productivity, presenting, within an interface of a device associated with the grower, the modified set of farming operations.