Know Why Predictive Analytics is the need for Businesses today with some top Predictive Analytics Tools

By POOJA BISHT |Email | May 30, 2019 | 2370 Views

To make any business successful and work for a longer time, a Proactive and forward-looking approach is needed and this is the only approach by which businesses plan strategies for the future. A future strategy is needed for gaining higher returns in business and at the same time preventing it from the unknown risks.  This is what offered from Predictive Analytics. Using Predictive Analytics businesses make use of their past and present data to predict future certainties. This article will highlight some of the top Predictive Analytics tools used by businesses today by highlighting the need for Predictive Analytics used in Businesses today.

What is Predictive Analytics?
Predictive Analytics is the branch of advanced analytics which uses historical and present data of any business or organization to predict the future trend. It uses data mining, predictive modelling and various techniques to make predictions for the future. It is true that the results offered by Predictive Analytics are mostly accurate and so organizations are dependent on it to know trends for the future.

Why Predictive Analytics has become so important for businesses?
Take the example of MacDonald. Every day a number of foodies go to MacDonald to enjoy their favourite food. Providing enough surplus food to the customers is the major responsibility of MacDonald. Also, it needs to keep in mind that no food gets wasted. All these things can be achieved using Predictive Analytics now. Using Predictive Analytics, the company uses a vast amount of historical data and is able to figure out when the traffic of the customers will be low or high so to optimize the food services. 

With the help of the software, the company accordingly manages its staffing and all other needs required to provide good customer satisfaction. Similarly, financial companies use Predictive Analytics to detect frauds, Healthcare sector uses it to diagnose chronic diseases and so on. Predictive Analytics provides the industry with so many useful insights that are needed by any organization to pace ahead and improve customer satisfaction.

Some Predictive Analytics tools:
  • IBM Predictive Analytics 
The software addresses all aspects of the entire analytical process; data collection, planning, deployment, analysis, and reporting and allows users to derive predictive insights from their data to improve the decision-making process, detect threats and predict the behaviour of the potential customers. A portfolio of applications: IBM SPSS Statistics, IBM SPSS Analytics Software, IBM SPSS Modeller, IBM Analytical Decision Management, IBM Social Media Analytics, IBM SPSS Data Collection, and SPSS Predictive 
Analytics Enterprise has included in IBM Predictive Analytics.
Features of IBM Predictive Analytics 
  1. Statistical analysis and visualization
  2. Predictive modelling and data mining
  3. Decision management and deployment
  4. Big data analytics
  5. Open source integrations
  • SAP Predictive Analytics
SAP Predictive Analytics is a business intelligence software from SAP.  The software is designed in such a way so as to help organizations in analyzing a large number of data sets and predict future events. The software builds predictive analytics models to identify unforeseen opportunities in the future and helps businesses to better understand their customers.
Features:
  1. Automate analytics with Python API
  2. Predictive Modelling
  3. Embedded Predictive Insights
  4. Support data privacy to achieve legal compliance

  • H2O
H2O is open-source software for big-data analysis and helps businesses in exploring datasets and finding relevant patterns out of it. The software is used for exploring and analyzing datasets which are held in cloud computing systems and in the Apache Hadoop Distributed File System. Also, the software is compatible with conventional operating-systems like Linux, macOS, and Microsoft Windows.
Features:
  1. Data Mining
  2. Uses Iterative methods to solve real-time problems
  3. Can run on Spark as well.
  4. Its graphical user interface is compatible with: Chrome, Safari, Firefox and Internet Explorer. 
  • Oracle Advanced Analytics
Detecting patterns and delivering actionable insights is effectively possible with the help of  Oracle Advanced Analytics. Oracle Advanced Analytics is a combination of Oracle Data Mining and Oracle R Enterprise
Features:
  1. eliminates data movement
  2. preserves security to anticipate customer behaviour
  3. text mining
  4.  statistical analysis
  5. advanced numerical computations 
  6. interactive graphics 

Source: HOB