4 Courses Offered
SAS (earlier known as Statistical Analysis System) is a software suite developed by SAS Institute for advanced analytics, business intelligence, data management, and predictive analytics. SAS brings many advantages to professionals dealing with big data analysis. There are many factors for the same. It has been around for a long time so there is wi
SAS (earlier known as Statistical Analysis System) is a software suite developed by SAS Institute for advanced analytics, business intelligence, data management, and predictive analytics. SAS brings many advantages to professionals dealing with big data analysis. There are many factors for the same. It has been around for a long time so there is wi
Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future, or otherwise unknown, events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities
Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future, or otherwise unknown, events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities
R is a programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. In recent times, one has seen the popularity of this software in the context of data analytics increase and our programs are geared to g
R is a programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. In recent times, one has seen the popularity of this software in the context of data analytics increase and our programs are geared to g
One of the biggest challenges large corporations face today is to store, manage and process their data. Today in the era of big data where in 90% of the worlds data is generated in the last two year, it is almost impossible to manage such data and generate faster results. A need to develop a framework which could manage data storage and processing
One of the biggest challenges large corporations face today is to store, manage and process their data. Today in the era of big data where in 90% of the worlds data is generated in the last two year, it is almost impossible to manage such data and generate faster results. A need to develop a framework which could manage data storage and processing
