Certified Data Analysis Program

Program Overview

The Certified Data Analysis Professional is a first-level, hands-on training course aimed at equipping participants with the necessary concepts and tools needed to perform basic statistical and analytics reporting activities, in order to generate value out of existing data. The course will provide participants with the knowledge required for understanding distinct methods used in the interpretation of statistical data. By attending this certification program, participants will be able to understand the basic methodology used in statistical interpretation of quantitative data and become proficient in using key Microsoft Excel features, histograms, and Pareto Charts.

Benefits

• Improve the organization's decision-making process by gaining knowledge on data analysis and interpretation;
• Obtain the most relevant data needed by setting up a customized data analysis process;
• Achieve management's buy-in by understanding the utility of implementing customized data analysis methodology in daily business activities;
• Provide a logical framework for understanding data analysis instruments.

Learning Objectives

• Develop a hands-on, practical overview of data analysis and connected topics;
• Integrate statistical concepts and analysis tools that are widely used in corporate analytics environments;
• Analyze examples of practical applications for statistical methods used in solving real-life business issues;
• Acquire mastery of basic MS Excel and statistical techniques through practical examples.

Participants' Profile

• The course is designed for anyone who has basic mathematical training and basic competences in using Microsoft Excel. Statistical knowledge, intermediate or advanced knowledge of Excel, practical experience with data analysis, and related duties are not necessary but may contribute to a better understanding and more in-depth coverage of the course content. Diversity of participants' backgrounds may help in a thorough coverage of the entire syllabus.
• The course is addressed to managers, HR representatives, analysts, auditors, or logistics and acquisitions experts, as well as to professionals from other business areas who deal with data analysis.
• The course may also be a starting point for those interested in pursuing career opportunities in data analysis, data modeling, and related activities (e.g., campaign management, data mining, statistics, risk management, reporting, data processing for survey analysis, etc.).

Key Business Benefits

• Achieve process clarity and strategy optimization by implementing data analysis frameworks;
• Optimize performance reporting processes by closing the gaps found in the data analysis tools;
• Attain superior results by implementing data analysis procedures.

Program Agenda

Day One: Understanding Data Analysis

• Course Context
  • Introduction of the participants;
  • Expectations setting;
  • Learning objectives formulation;
  • Course agenda presentation.
• Data Analysis - The Basics
  • Definitions and utility of data analysis;
  • Data analysis process;
  • Realignment based on analysis;
  • Governance of data analysis.
• Data Quality
  • Data accuracy;
  • Logical inconsistencies;
  • Data sampling errors;
  • Data comparability;
  • Data completeness;
  • Economic/business interpretation of qualitative data.
• Organizing, Synthesizing, and Aggregating Data
  • Data structure;
  • Challenges in aggregating data;
  • Data preparation;
  • Expert judgment;
  • Meta-analysis and evaluation synthesis;
  • Normalization of data.

Day 2 - Data Analysis

• Statistical Analysis Tools
  • Statistical tools: mean, median & mode;
  • Trend analysis: variance and standard deviation;
  • Hypothesis testing;
  • Statistical process control.
• Data Visualization and Pattern Detection
  • Single, two, and multi-dimensional data visualization;
  • Level, trend, seasonality, and noise in time series data;
  • Autocorrelation.
• Data Comparison
  • Analysis using histograms and Pareto Charts;
  • Cumulative percentage analysis;
  • Rules for interpreting data and formulating conclusions.
• Univariate and Multivariate Analysis
  • Differences and complementarities in single and multivariate analyses;
  • Techniques used in analyzing single variables;
  • Techniques for analyzing relationships between variables (correlation analysis);
  • Parametric vs. non-parametric techniques used for analysis.
• Regression Analysis
  • Linear and logistic regression;
  • Assumptions and basic models;
  • Diagnostic measures and uses;
  • Nonlinear models using categorical data and other topics of interest.

Day 3 - Advanced Data Analysis

• Probability and Confidence
  • Expected values and hypothesis testing;
  • Contingency tables - ANOVA.
• From Exploratory to Predictive Modelling
  • Expected values;
  • Confidence limits;
  • Risk and uncertainty;
  • Type 1 and type 2 errors;
  • Tentative sensitivity analysis.
• Data Dimensionality
  • Compensation for small sample sizes;
  • Big Data.
• Review and Certification Exam
  • Course review;
  • Certification Exam.

Facilitator

• Adrian Ooiu, Subject Matter Expert, The KPI Institute.
• Adrian Ooiu is a subject matter expert for The KPI Institute and has gained 15 years of experience in statistical, economic, and business analysis in various roles within the government, academic organizations, and multinational corporations.
• Throughout his experience, he has garnered work expertise and undergone training in the following fields: labor market, health economics, migration, quantitative marketing - including online surveys, composite indicators, default and risk models, business analytics and business intelligence, data preparation and processing, and teaching and coaching.
• The work he has been performing includes doing statistical analysis by using the following main methods: regression analysis, including logistic analysis, panel data/hierarchical models, factor and PCA analysis, Bayesian regression analysis, cluster analysis, market basket analysis, decision trees, and natural language processing.

Learning Experience

• Pre-course: Participants are required to take the following steps to ensure a smooth transition to the face-to-face training:
  • Needs assessment - complete a questionnaire to determine a tailored and relevant learning experience;
  • Pre-course evaluation quiz - take a short quiz to establish the current level of knowledge;
  • Guidance and schedule - analyze a document presenting guidelines on how to maximize the learning experience;
  • Forum introduction - share an introduction message to present oneself to the other course participants;
  • Expectations - share expectations regarding the training course;
  • Pre-requisite reading - go through a series of documents to better understand the core course content.
• Core Course: The Certified Data Analysis Professional training course provides an interactive practice-based learning environment in which participants focus on:
  • Establishing customized models for data analysis based on the organization's requirements;
  • Gaining knowledge on basic (and advanced) data analysis concepts and statistical instruments;
  • Applying the knowledge gained in practical exercises aimed at strengthening the learning process.
• After-course: The learning process is not finalized when the core course ends. In order to benefit from a complete learning experience, participants are also required to take the following steps:
  • Forum discussions - initiate a discussion on the forum and contribute to a discussion opened by another participant;
  • Action plan - create a plan for the actions and initiatives intended to be implemented after the training course;
  • In-house presentation - create and submit a short PowerPoint presentation to share the knowledge acquired within the training course with colleagues;
  • Additional reading - go through a series of resources to expand content-related knowledge;
  • Learning journal: reflect upon the 3 stages learning experience and complete a journal.
• Certification Process: The certification process is finalized only when all 3 stages of the learning experience are completed. Nonetheless, participants will receive:
  • Certificate of Completion (soft copy): after completing pre-course activities and passing the Certification Exam;
  • Certificate of Attendance (hard copy): after participating in the 3 days on-site training course;
  • Certified Data Analysis Professional Diploma (hard copy): after successfully completing all 3 stages of the learning experience.

Madinah Institute For Leadership And Entrepreneurship (MILE)

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Overview:

The Madinah Institute for Leadership and Entrepreneurship (MILE) is a non-profit organization dedicated to fostering leadership and entrepreneurial excellence within the Arab and Muslim world. It was established as a Corporate Social Responsibility initiative of Madinah Knowledge Economic City (KEC) and has since grown into a collaborative effort supported by various companies, academic institutions, research and consulting organizations, and professional groups.

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Services Offered:

MILE offers a range of services, including:

Executive Education Programs:

MILE provides various programs designed for senior executives and high-potential leaders, covering topics like leadership, management, public policy, and strategic foresight.

Consulting Services:

MILE offers consulting services in areas such as strategy, organizational development, human capital, and performance development.

In-house Training:

MILE provides customized in-house training programs tailored to the specific needs of organizations.

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Student Life and Campus Experience:

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Key Reasons to Study There:

Global Thinkers:

MILE brings together renowned global thinkers and experts to share their knowledge and insights.

Scholarship Opportunities:

MILE offers scholarships to support talented future leaders and provide them with networking opportunities.

Holy City of Madinah:

The institute is located in Madinah, a significant religious and historical city, offering a unique cultural experience.

Partnership Opportunities:

MILE provides opportunities for organizations to collaborate and contribute to the development of business leaders.

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Academic Programs:

MILE offers a variety of programs, including:

Program for Advanced Leadership & Management (PALM):

This program focuses on transforming senior executives into leaders by providing them with the latest management concepts and tools.

Certified PPP Professional (CP³P):

This program aims to develop APMG-certified professionals in Public-Private Partnerships (PPP) to address infrastructure challenges.

Executive Program for Developing and Implementing Public Policies:

This program focuses on public policy challenges and aims to enable the development of high-performing governments.

Strategic Foresight and Scenario Analysis:

This program focuses on strategic foresight and scenario analysis techniques.

Advanced Program for Excellent Government Performance:

This program is designed for high-potential leaders in government agencies and features renowned professors and experts in public administration.

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Other:

MILE has a strong alumni network and provides various resources for its alumni, including profiles, testimonials, and networking opportunities. The institute also offers a range of publications and webinars.