Data Analysis and Information Management Course

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We are proud to offer this course in a variety of training formats to suit your needs. We use the highest quality learning facilities to make sure your experience is as comfortable as possible. Our face to face calendar allows you to choose any classroom course of your choice to be delivered at any venue of your choice - offering you the ultimate in convenience and value for money.

June 2024

Code Date Duration Location Fee Action
DAI006 24 Jun 2024 - 28 Jun 2024 5 days Cape Town, South Africa $2,400 Register
DAI006 24 Jun 2024 - 28 Jun 2024 5 days Nairobi, Kenya KES 83,000 | $1,100 Register
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June 2024

24 Jun - 28 Jun 2024
5 days
Cape Town
24 Jun - 28 Jun 2024
5 days
KES 83,000 $1,100
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Everyone agrees that evidence-based decision making is the key to corporate high performance. In a world where everything is now measured and recorded, the data that companies hold can be a very rich and powerful source of evidence, but only if it can be analyzed and interpreted accurately and reliably. This Data Analysis and information course shows participants, by example, how to analyze and interpret data and hence how to make robust and defensible evidence-based business decisions.

The Data Analysis training course shows participants how to use Microsoft Excel to perform a wide range of powerful analysis and interpretations, using real data. This is possible because, although most people are familiar with Microsoft Excel, they generally only use a small fraction of its true capability. The course will show participants how to make the most of Excel by explaining and demonstrating many of the very powerful analytical, visualization and interpretation capabilities.


5 Days

Who Should Attend

Professionals working in the following fields:

  • Performance assessment and monitoring
  • Planning
  • Data analysis
  • Management and leadership
  • Finance
  • Human resources
  • Quality control

Engineering and technology

Course Level:

Course Objectives

At the end of this IRES training course, participants will learn:

  • A good understanding and extensive practical experience of a range of common analytical techniques and interpretation methods for numerical data
  • The ability to recognize which types of analysis are best suited to particular types of problems
  • The ability to judge when an applied technique will likely lead to incorrect conclusions
  • A good understanding of a wide range of common statistical methods and approaches
  • The ability to use Microsoft Excel 2016, 2019 or 365 to analyze and interpret a wide range of real data types
  • Experience of how to transform numerical data into evidence and hence how to make informed business decisions

Course Outline

Module 1; Logical and Reliable Data Analysis, Descriptive Statistics, and Pivot Tables

  • Importing data into Excel
  • Best practice when analyzing data
  • Analyzing and representing coded data
  • Descriptive statistics and their real meanings
  • Performing a frequency analysis
  • The use of pivot tables and pivot charts
  • Noisy and incomplete data, statistical significance and dealing with outliers

Module 2; Data Mode Shape Analysis

  • Plotting data against time
  • Generating data mode shapes
  • Fitting curves to data
  • Correlating mode shape to time-based events
  • Interpreting time series analyses
  • Moving average calculations

Module 3; Scenario Analysis and Interactive Spreadsheets

  • Representing analytical problems as multi-input, single-output (MISO) systems
  • Deterministic systems analysis
  • What if and visual scenario analysis
  • Dynamic / interactive spreadsheets and the use of forms control
  • Moving window, conditional and adaptive calculations
  • Measuring the sensitivity of calculated variables

Module 4; Regression Analysis and Correlation

  • Equations of curves
  • The prediction of future behavior using data shape – regression analysis
  • Linear, polynomial, exponential and power curve fits
  • The dangers of over-fitting
  • Data end effects
  • Goodness of fit (sum of square error – SSE) and R2
  • Evaluating equations, solving equations, and using Solver
  • Correlation and causality

Module 5; Data Driven Methods and Analysis of Variance

  • Non-deterministic system
  • Data driven methods
  • One step ahead future prediction using data science (multivariate correlation)
  • Single factor analysis of variance (ANOVA)
  • Two factor analysis of variance
  • A demonstration of artificial intelligence – the travelling salesman problem

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Course Administration Details:


The instructor led trainings are delivered using a blended learning approach and comprise of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.


Upon successful completion of this training, participants will be issued with an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).


The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.


Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer.

Email:[email protected]/[email protected]

Mob: +254 715 077 817/+250789621067


This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817/+250789621067

Mob: +254 792516000+254 792516010 , +250 789621067 ,or mail [email protected]/[email protected]


Payment should be transferred to IRES account through bank on or before start of the course.

Send proof of payment to [email protected]/[email protected]

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