Improve Your Offering with Big Data & Predictive Analytics
Folio3 effectively utilizes big data and predictive analytics to help businesses achieve their goals in today’s data-centric world. We apply a range of machine learning techniques to identify and understand patterns in historical data and make future predictions, providing companies with long-lasting competitive advantages. Our predictive analytics applications can be used for fraud detection, business forecasting, customer behavior prediction, analysis of life sciences data, credit risk assessment, and so forth
Predictive Analytics Company - Folio3
Folio3’s Predictive Analytics Solutions drive fast and effective results, enabling you to identify opportunities and anomalies in your business processes and strategy. Our applications analyze customer lifecycles and preferences through data, allowing companies to eliminate risks and reduce uncertainties while improving offerings and providing better customer service. Furthermore, we also combine our machine learning expertise and sophisticated data gathering techniques to implement predictors, allowing companies to take appropriate measures at the right time, reducing cost with minimal effort.
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Enhanced Sector Analytics and Departmental Efficiency with Predictive Analytics
Predictive Analytics Solutions by Folio3 company has a number of uses cases and can be applied in various sectors like retail, banking, insurance, telecommunications, healthcare, pharmaceuticals and so forth. Analytics generated by our solutions can also improve different business areas like HR, Marketing and overall business performance by identifying deficiencies, making accurate forecasts, and increasing operational efficiency.
Predictive Analytics Company - Machine Learning Key Capabilities
Our expert business analysts and data scientists build sophisticated predictive analytics solutions using automation. These can be embedded in business processes in no time.
We offer end-to-end predictive analytics solutions management, whereby regular updates are provided for better performance.
Provide predictive models for different frameworks to fragmentize variables, analyze them and facilitate predictive scoring in real-time.
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Predictive Analytics FAQ
What are the best predictive analytics solutions use cases in healthcare?
Predictive analytics is being adopted by various industries including marketing, law, manufacturing and health care. Many stakeholders of the health care sector are benefiting from this advanced technology. Widespread usage of the internet and the smartphone has enabled users to access large amounts of data at a click of a button. Health care industry in particular has digitised many of its operations, as this allows them the ease of workflow, faster information access, reduce costs and improve the quality of their health service. From enhanced accuracy of diagnosis and treatment to identification of potential risk factors and insights to enhance cohort treatment, Predictive analytics, in health care helps manage overall operations in a more productive manner. Using predictive analytics to make informed decisions, health care providers can improve their long-term relationship with patients. However, usage of predictive analytics requires centralisation of data which can prove to be risky if proper processes are not in place. However, predictions made solely for the sake of making a prediction are a waste of time and money. Moreover, in healthcare, predictive analytics can only prove useful if the knowledge can be transferred into action.
What are the best predictive analytics examples?
Predictive analytics in the health care sector is focused primarily on the probable outcomes of an individual’s health. By analysing historical data, predictions can be made on the likelihood of a patient contracting a disease and their susceptibility to Central-Line Associated Bloodstream (CLAB) infections. Moreover, such cognitive services process can also help determine the risk of a patient not showing up for scheduled appointments. Health Catalyst is one such company operating in Salt Lake City since 2008 that specialises in the focus areas mentioned above. Find more examples HERE!
Predictive analytics solution is a part of machine learning or RPA?
The purpose of Robotic Process Automation (RPA) is to automate repetitive tasks, thereby reducing the processing time significantly. Unlike AI, RPA relies heavily on rules-based framework. With Machine Learning on the rise, RPA enables vendors to create a connection between execution and decision making in an automated environment. Powerful symbiosis of Machine Learning with RPA in an integrated and strategic manner does not just enhance data processing but also decision making. AI fields such as machine learning, predictive analytics and sophisticated cognitive computing combined with RPA allows the intelligence to pick up on patterns and direct RPA to act accordingly. As more data gets examined and trained, RBA becomes more intelligent over time and can help increase worker performance, reduce operational costs and response times.