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Data Analytics: Discovery the Hidden Structure, Model Building Approach


In many organizational and sectoral situations, conflict about how to monitor the performance of the organization either via score card or dashboard, is always the subject of debate and mind struggling among executives. Lacking the methodology of building a robust as well as rigorous score card became the chronic problem of many organizations. Despite the availability of Information and Data inside the data warehouses of the organization, nevertheless the challenges are always; how to make sense out of these overwhelming Information.

Risk Management, and Predictive Analytics are among the critical issues discussed during board meetings and gathering. Despite the fact that those issues are crucially needed, nevertheless, the current internal skills and knowledge about the appropriate techniques are still lacking which therefore requires hiring very expensive consultant firms or individuals to the job and hence no chance for internal development.

Objective and Scope

Data Analytics Technologies and Solutions (DATAS) are very expensive and it is considered one of the highest investments in any competitive corporation. Decision to choose the appropriate DATAS requires certain level of knowledge inside the corporation.

This Program is focusing on helping participants, mainly; executives to choose and build the most appropriate quantitative model(s) that suits the organization needs. One of main targets of this program is to pave the fundamental quantitative background required for future model building when external and internal environment changes.

Key Issues to be covered:

  • Reviewing the current Knowledge: The Quantitative Background
  • Identifying the Problem and the Objective of the Model Building
  • Identifying the Key Variables needed for the Model Building
  • Determining the Type of Data, and the Measuring Scales (continuous versus discrete, metric versus nonmetric)
  • The Importance of Probability Distributions and its Applications
    • Probability Concepts – Probability Based Decision Making
    • Type of Probabilities
    • Discrete and Continuous Distributions – The Meaning of Distributions and its applications and importance in Decision Making Process
  • The Use of Monte Carlo Simulation for Risk Analysis
  • Measuring and Quantifying the Impact (Data Analytics) –
    • Differences and Relationships
    • Tools for Assessing the Significance of the Impact: t-tests, F-test chi-square test
  • Correlations and Linear Regressions for Predictive Model Building
  • Multivariate Data Analysis Tools Kit: The Data Mining Foundations

o    Scoring and Classification: Logistic Regression, Discriminant Analysis

o    Segmentation and Data Reduction: Cluster Analysis, Factor Analysis

o    Design of Experiment: Conjoint Analysis, ANOVA, ANCOVA

o    Artificial Neural Network

Learning Objective and Skills to be Acquired

Participants of the program will learn:

o   How to identify and validate the organizational problem and issue

o   How to conceptualize the business problem by developing the appropriate framework

o   How to determine the needed data and information for decision making

o   How to select the appropriate model building method

o   How to build a robust model and how to interpret the information from data analysis outputs

o   How to validate the final model

Duration and Delivery

This program will require 24 Instruction hours which can be delivered during suitable time span as per client needs, as an example.

Important Note: Participants must have a sound quantitative background (KWANTi1™ or equivalent is prerequisite). Also they need to bring their laptop with Microsoft Excel installed during the program. For advanced quantitative tools, another Statistical package will be used (free trial license will be installed).