What is Predictive Analytics and why is it needed
These days, companies doing business has lot of information which keeps growing exponentially. The challenge here is to convert this huge volume of information into knowledge which could help them in elevating their business value, and that too real time. There are many analytical tools available in the market these days. But these tools are based on historical data and can help companies to understand what went wrong in the past. Predictive analytics helps to get the insights (real time) of the customer behavior so that companies can act accordingly, which in turn could increase their profitability and business value.
In Wikipedia, Predictive Analytics is defined as following:
Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining and game theory that analyze current and historical facts to make predictions about future events.
In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision making for candidate transactions.
Predictive Analytics is used in various industries like healthcare, consumer products companies, oil and gas, insurance, retail etc.
SAP Predictive Analytics, Powered by HANA
Predictive Analytics together with the power of in-memory technology can reduce the time and cost of processing the voluminous data. It provides intuitive design options to users so that usage of Predictive Analytics is not limited to a certain group of trained people but also to business users.
Trends in Predictive Analytics
Though the concept of Predictive analytics has been around for quite some time, it used to be mostly implemented by large companies. But these days the trend is changing. Many companies understand the value that predictive analytics brings in and are capitalizing on it to solve a wide range of issues in various applications. Also, text data is given more importance these days other than just processing numerical data.
Other interesting Reads(includes content from other website)
· * IBM’s Watson Solution for Healthcare industry :