Big Data and Predictive Analytics
Predictive analytics is the art of using analysis to predict trends, behaviors, and conditions. Organizations and governments can then enable quick, accurate forecasting and act on opportunities before they manifest.
Predictive solutions can support a variety of business functions, including marketing and merchandising, sales, and risk management. For example,
- Banks can use predictive solutions to assess the likelihood of loan default
- Insurance companies can use it to determine risk and set premiums accordingly
- Local law enforcement agencies can use it to forecast when and where crimes are most likely to take place
- Manufacturers can leverage it to anticipate warranty claims or defects
Big Data provides extra insight when coupled with predictive solutions. The additional data helps strengthen and reinforce the probability of a future outcome or occurrence. However, your big data needs to be properly cleansed in order to produce the desired results. It’s obvious that the accuracy of the results delivered by predictive analytic solutions is heavily reliant on the integrity of the underlying data.
Once any data quality problems are rectified, your organization can enable effective decision management with your big data by applying business analytics technologies. The results of analyzing big data with those technologies are then distributed to management and workers which allow them to be proactive with their decision-making.
To help organizations conquer their big data, Information Builders developed iWay Big Data Integrator, a native Hadoop solution that includes data ingestion, transformation, and data quality.
For an integrated solution for BI, data modeling, and scoring, try WebFOCUS RStat. With RStat, companies can easily and cost-effectively deploy predictive models as intuitive scoring applications, so business users at all levels can make decisions based on accurate, validated future predictions instead of relying on instinct alone.