For clients without Chief Data Scientists, this service is vital to defining the current status vis-a-vis business goals and how data will best support accomplishing the articulated goals. A data strategy also helps with such practicalities as identifying highly valuable data and differentiating between structured and unstructured data sets. Ultimately, a data strategy allows leaders to manage data like assets rather than byproducts of business activity.
Sorting through and defining different types of datasets underpins a good data strategy, defining how a particularly company or project will benefit from a particular AI solution. Typically, growing pains, organizational changes, or leadership changes necessitate organizations to create or revisit data strategies.
Sometimes we do light reorganization with our clients before moving forward. And sometimes our clients need us to go a step beyond. In these cases, our team of data scientists will partner with chief information and product officers to architect usable, shareable, moveable data sets before we engage in a project that leverages these powerful assets. Our approach to data strategy allows clients to take an iterative, evolutionary approach.
The type of strategy depends on the amount and type of data; older companies with legacy data or that are undergoing an organizational change often need these services most. Young companies building products that rely on compiling data need to focus on data strategy from the get-go. Learn more!
How Farm Journal Used Data Strategy to Transform its Business With nearly 150 years serving the agriculture market, Farm Journal had an invaluable wealth of industry knowledge. Grey Montgomery, Farm Journal’s President of Data and Research, wanted a data strategy that would spark innovation and serve as a roadmap to construct an expansive, trusted data…