Data Analytics and Business Decision Making

Start Date End Date Venue Fees (US $)
03 May 2026 Riyadh, KSA $ 3,900 Register
02 Aug 2026 Manama, Bahrain $ 4,500 Register
20 Dec 2026 Dubai, UAE $ 3,900 Register

Data Analytics and Business Decision Making

Introduction

This training course highlights the significant value that data analytics can offer as a tool to support management decisions. It demonstrates the role of data analytics in guiding strategic initiatives, informing policy decisions, and enhancing operational decision making. This Course emphasizes the practical applications of data analytics in management, focusing on accurate interpretation and effective integration of quantitative insights into managerial decision-making processes. Exposure to data analytics will build participants' confidence in using evidence-based information to reinforce management decisions.

This training course will feature:

  • In-depth discussions on data analytics applications in management.
  • Insights into the importance of data within data analytics.
  • Practical application of analytical methods through examples.
  • Emphasis on management’s interpretation of statistical evidence.
  • Guidance on integrating statistical thinking into everyday work.

Objectives

    By the end of this Training Course, participants will be able to:

    • Recognize the role of data analytics as a support tool in decision making.
    • Understand the scope and structure of data analytics.
    • Apply a range of relevant data analytics techniques.
    • Interpret and critically assess statistical evidence.
    • Identify applicable uses of data analytics in their work environment.

Training Methodology

This Training Course utilizes proven adult learning techniques to maximize understanding, retention, and practical application. Daily workshops are interactive, involving discussions on applications and hands-on practice with data analytics using Microsoft Excel. Participants are encouraged to bring data from their own work environments, adding relevance to the learning experience. Emphasis is placed on valid interpretation of statistical evidence within a management context.

Who Should Attend?

This Course is suitable for a diverse range of professionals, particularly those who will benefit most from:

  • Holding management support roles.
  • Working as analysts who frequently deal with data and analytics.
  • Seeking to enhance decision-making through data analytics insights.

Course Outline

Day 1: Setting the Statistical Scene in Management

  • Introduction; The quantitative landscape in management

  • Thinking statistically about applications in management (identifying KPIs)

  • The integrative elements of data analytics

  • Data: The raw material of data analytics (types, quality and data preparation)

  • Exploratory data analysis using excel (pivot tables)

  • Using summary tables and visual displays to profile sample data

Day 2: Evidence-based Observational Decision Making

  • Numeric descriptors to profile numeric sample data

  • Central and non-central location measures

  • Quantifying dispersion in sample data

  • Examine the distribution of numeric measures (skewness and bimodal)

  • Exploring relationships between numeric descriptors

  • Breakdown analysis of numeric measures

Day 3: Statistical Decision Making – Drawing Inferences from Sample Data

  • The foundations of statistical inference

  • Quantifying uncertainty in data – the normal probability distribution

  • The importance of sampling in inferential analysis

  • Sampling methods (random-based sampling techniques)

  • Understanding the sampling distribution concept

  • Confidence interval estimation

Day 4: Statistical Decision Making – Drawing Inferences from Hypotheses Testing

  • The rationale of hypotheses testing

  • The hypothesis testing process and types of errors

  • Single population tests (tests for a single mean)

  • Two independent population tests of means

  • Matched pairs test scenarios

  • Comparing means across multiple populations

Day 5: Predictive Decision Making - Statistical Modeling and Data Mining

  • Exploiting statistical relationships to build prediction-based models

  • Model building using regression analysis

  • Model building process – the rationale and evaluation of regression models

  • Data mining overview – its evolution

  • Descriptive data mining – applications in management

  • Predictive (goal-directed) data mining – management applications

Accreditation

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