Predictive analytics

Predictive analytics is a branch of advanced analytics used to predict unknown future events, such as customer behavior, product demand, and even disease outbreaks.

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Predictive analytics services

Predict future sales factors using the Predictive Analytics engine
Failure prediction on the production line can help prevent outages
Foresee changes in the health of patients to properly adjust the treatment plan

Predictive analytics uses a variety of techniques including data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about the future. It predicts the probability of future outcomes based on a dataset of past events (called a training set). Future actions can be defined by these predictions.

Predictive analytics can be used in many fields, such as sales, marketing and healthcare. For example, it can predict sales factors, customer behavior, product demand, and even disease outbreaks. Predictive analytics can be used by companies, governments, and individuals to help them make better decisions about all aspects of their operations. Companies such as Amazon and Netflix use predictive analytics to determine what products are likely to be popular with customers—and then they stock/advertise those products accordingly. Predictive analytics is also used by governments to determine whether new policies will be effective, based on how similar policies worked in the past.

With us you can

Use sales data with the Predictive Analytics engine to make informed decisions about which strategies work best.

Leverage the medical data of patients to predict exacerbations of the disease.

Precisely measure and predict the behavior of customers to estimate revenue.

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Our experience

  • Predicting pulmonary disease exacerbations
  • Using historical patient data combined with real-time analysis of multiple data sources, including a custom-made device, we are able to predict exacerbations in patients with asthma or COPD.
  • Estimating time spent on a linguistic project
    Prediction of time estimation on linguistic tasks in not easy, as every text has different subject, terminology, and complexity. Predictive analytics connected with Natural language processing (NLP) helps predict time spent on a linguistic task with high accuracy.
  • Forecast of plant growth based on satellite data

By retrieving data from satellites and using it to predict changes in crop growth, flooding and landform, the output is crucial for precision agriculture and transportation planning.