What is Predictive Analytics? Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown future events. Predictive analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future. It uses a number of data mining, predictive modeling and analytical techniques to bring together the management, information technology, and modeling business process to make predictions about future. The patterns found in historical and transactional data can be used to identify risks and opportunities for future. [...]
Top 27 MS Data Science Schools 2018 : According to Mckinsey Global Institute report, by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with data science knowledge for the analysis of bigdata to make effective decisions. Many universities offers masters and other programs in data science and predictive analytics to fill the resource requirements in Bigdata and Predictive Analytics.These programs provides training both in management and data analytics.
Top 27 MS Data Science Schools 2018: Top Predictive Analytics, [...]
Predictive Pricing Platforms uses data science and machine learning to produce competitive pricing by considering a number of internal and external parameters such as competitor pricing, market, demand and supply. These are software-as-a-service-based, B2B solutions which can be integrated with customers e commerce systems and different from conventional pricing intelligence solutions which are rules based, in their use of data science and machine learning algorithms to increase sales and improve profits and margins. Blue Yonder Platform, Pricefy, PROS, Model N, Retalon, Zilliant, PriceGrid, Upstream Commerce, ECOPA Prezzu, Prisync are some of the top [...]
Predictive Lead Scoring Software: Lead scoring is a very useful system for measuring a prospect’s likelihood of buying. Lead scoring is used to rank prospects against a scale that represents the perceived value each lead represents to the organization. The resulting score is used to determine which leads will engage and in the order of priority. A score can be arrived by considering the prospect’s previous interactions with the organisation along with other external data points and signals, such as demographics and prospects behaviour attributes from various other data sources. This can be achived by connecting organisations customer relationship [...]