Without the right technology – and the right data – many analytics and ML projects never get off the ground.
The harsh reality is that most AI initiatives fail long before they ever reach the algorithm stage. That said, the sheer breadth of open source tools, along with innovations in cloud technology, have simplified predictive algorithm design – once a major limitation. This forces companies looking for an edge to go beyond their models and tools, identifying new areas for improvement. The biggest of these is data. Organizations must now figure out how to operationalize their ability to access and leverage the right data for any business challenge.
In this whitepaper, we’ll reveal the new paradigm emerging in data asset strategy. We’ll also present solutions for data teams looking to adopt the model across the entire alternative data acquisition cycle.