Leading organizations are embracing advanced analytics as they start to realize the vast opportunities and leverage analytics can bring to solving their complex business problems.
While the traditional analytical tools that comprise basic business intelligence (BI) examine historical data, tools for advanced analytics focus on forecasting future events and behaviors, allowing businesses to conduct what-if analyses to predict the effects of potential changes in business strategies.
Predictive analytics, data mining and machine learning are just some of the analytical techniques that fall under the heading of advanced analytics. These technologies are widely used in industries including marketing, energy, healthcare, risk management, and economics.
Approximetricsemploys the use of these advanced analytics techniques to guide insights into business processes

Machine Leaning
  • Rule Induction
  • Neural Networks
  • Genetic Algorithms
  • Fuzzy Logic
  • Hidden Markov Model
  • Suppot vector machine
  • Self-Organizing Maps
Descriptive Analytics
  • Factor Analysis
  • Bivariate and multivariate analysis
  • Inferential Statistics
Predictive Analytics
  • Regression Model
  • Chaid
  • Decison Tree
  • Cluster Analysis
  • Naïve Bayes classifier
Text Analytics & Social media Analytics
  • Document clustering
  • Keyword Analysis
  • Natural Language Processing
  • Serarch & Information Retreival
  • Sentiment analysis
  • Latent semantic analysis
Optimization and Simulation
  • Monte calose
  • Ranking and selection
  • Response surface methodology
  • Lipschitzian optimization
  • Metaheuristics
  • Stochastic approximation techniques