Look into the future with the help of machine learning and deep learning models
PREDICTIVE ANALYSIS
Predictive analytics enables predictions through stochastic analyses based on internal company data and external market data. Social media also plays an important role in many use cases, especially when it comes to customer opinions and the prediction of customer behaviour.
Typical use cases include predicting customer demand and warranty cases in retail, predicting loan defaults and creditworthiness in the financial world, and tenant scoring in the real estate industry. In industry, predictive analytics plays a role especially for logistics planning, for quality monitoring as well as for maintenance as predictive maintenance.
With DQ Predictive Analytics, you get faster and more accurate models for your forecasting, protect yourself against critical failures and can also automate your operational decision-making processes.
CLASSIFICATION OF BUSINESS EVENTS
Our algorithms label your business events with class labels so that, for example, customer orders with an increased likelihood of returns or machine runs with an increased risk of failure or rejects are flagged for early detection
REGRESSION OF BUSINESS VALUE
Our regression models enable the prediction of sales, quantified requirements, reasonable prices or even machine conditions
TIME SERIES
Predictive analytics is also the right choice for forecasting values over time
PREDICTIVE MODELLING
We use classic machine learning, deep learning or collectives of learning algorithms (ensemble learning) to develop decision models for your challenges such as churn prediction, scoring, demand analysis or predictive maintenance
SOCIAL MEDIA
Predictive analytics becomes particularly powerful when data from social media or other internet platforms is included. We enable the connection of such unstructured data, for example for a customer loyalty analysis (churn prediction)
AUTOMATION
Our decision modeling can also be automated, for example for predictive and automated quality monitoring, maintenance (predictive maintenance) or purchasing planning (predictive order analytics)