Machine-learning-driven data preparation, insights and visualizations give analysts a head start.
This drives productivity and innovation as experts can focus on higher value-added tasks.
Data scientists and manufacturing specialists can examine production lines to determine what data can be used to predict future failures and how to best collect it. A recent (2018) report on the manufacturing industry saw 31% of manufacturing CEOs expecting artificial intelligence and machine learning to contribute to a reduction in operating costs. Learn how predictive maintenance helps make this reality.
For many businesses, demand planning is essential. Profitability, cash flow, and customer satisfaction and retention all hinge on getting this right. This white paper will introduce latent matrix factorization to model demand curves and discuss how it can be used to achieve these outcomes.
Introducing a machine learning based segment view about your customers gives the opportunity to improve conversions and lower customer acquisitions. Learn more how a sophisticated segmentation model, based on your existing data, can increase the number of customer purchasing and your campaigns' success rate by 40%.
Changes in the global business environment have driven a need for faster insights and decisions. In response to these changes, a global American software company approached Starschema about developing a solution for personalized, easily accessible and highly actionable financial insights.