Big Data Integration

Big Data Integration

1. Business Analytics

   • is the business and technological discipline dedicated to the continuous and iterative exploration and analysis of an organization's past performance to obtain insights (deep knowledge) and direct future planning
     • Used
       • Decision Optimization
         • It serves to replace decision making based on intuition or past experience with decisions driven by validated data and statistical evidence
         • Competitive Advantage Generation
           • It is used to identify hidden patterns or emerging trends before the competition
           • Continuous Performance Improvement
             • It serves to monitor constantly the success or failure of implemented strategies
     • Types of Business Analytics
       • Descriptive Analytics (DA)
         • It interprets historical data sets for a certain timeframe to identify valuable trends and patterns. It uses current data to provide insights that help corporations manage and/or improve their business processes
         • Predictive Analytics (PA)
           • It applies statistics, statistical combinations, and Machine Learning (ML) utilizing on hand data to forecast future trends or outcomes with the final objective of improving corporate performance
           • Prescriptive Analytics (PrA)
             • It uses mathematically or computationally techniques to obtain an outcome that will give the optimum result in a given scenario. It examines opportunities, correlations, and influences to produce the finest solution in real-time

2. Data and Statistical Methods

   • are the mathematical and scientific framework that allows analysts and data scientists to manipulate, explore, model, and infer information from data sets
     • used
       • Uncertainty Measurement (Inference)
         • It serves to quantify the risk and reliability of conclusions drawn from a sample of data
         • Hypothesis Validation
           • It is used to determine if an observation or strategic change has a statistically significant effect or is due to chance
           • Rigorous Modeling and Prediction
             • It serves to construct the mathematical algorithms that drive Predictive and Prescriptive Analytics
     • Types of Data and Statistical Methods
       • Descriptive Statistics
         • Its purpose is to summarize and describe the main characteristics of a data set
         • Inferential Statistics
           • Its purpose is to draw conclusions about a population from a sample and measure the uncertainty of those conclusions
           • Advanced Techniques (ML and Data Mining)
             • Advanced techniques that merge DSM with Machine Learning (ML) and Data Mining, addressing the complexity of Big Data