Date Venue Fee
19 Aug - 23 Aug 2024 Dubai – UAE $ 4,950 Register Now
11 Nov - 15 Nov 2024 Dubai – UAE $ 4,950 Register Now
23 Dec - 27 Dec 2024 London - UK $ 5,950 Register Now
02 Jun - 06 Jun 2025 Dubai – UAE $ 4,950 Register Now
18 Aug - 22 Aug 2025 Dubai – UAE $ 4,950 Register Now
10 Nov - 14 Nov 2025 Dubai – UAE $ 4,950 Register Now
22 Dec - 26 Dec 2025 London - UK $ 5,950 Register Now
About the Course

The world is under a lot of pressure and stress within the whole range of industries. The global pandemic has influenced everything, and the world and industries have shown that they are hyper-depended on data analytics. This phenomenon of modern times requires people to acquire knowledge and skills for proper gathering, analysis, and final understanding and use of the data. This Data Analysis Techniques training course provides comprehensive information on a complete set of Data Analytics, Analysis Techniques, and software used to analyse the available Data.

In whatever area we work in, new data is available, and the ability to extract, model and analyse information is a make-it-or-break-it issue today as well as in the industries of the future. Data Analytics helps enterprises identify trends and adjust operational procedures to harness the results, increase revenue and client experience, and identify, avoid or tackle the risks within the business environment.

Living in a data-rich age, we must understand that analysing and extracting true meaning from our business’s digital insights is one of the primary drivers of success. This training course focuses on the colossal volume of data we create daily. It will benefit the delegates how to analyse the data as, with so much data and so little time, knowing how to collect, curate, organise, and make sense of all of this potentially business-boosting information, as well as ensure business sustainability.

Core Objectives

Delegates will achieve the following objectives:

  • Understand the importance of Data for the digitalised world
  • Appreciate when to apply Data Analytics
  • Choose Appropriate Models and Technology for Data Analytics
  • Learn from the best examples of Data Analytics usage
  • Achieve results from Data Analytics
Training Approach

The delegates will be taught through learning techniques that ensure maximum understanding, comprehension, and retention of the information presented. The training methods will vary depending on their needs, from front-end to blended learning. It is divided through Information receiving, participation, and Learning by Doing to provide the highest level of apprehension and retention of the presented material. They will be working on case studies and doing a hands-on project, and at the end of the training course, they will be assessed to determine the level of knowledge they have retained.

The Attendees

This training course is designed and appropriate for anyone included in the Data Analytics process, which in today’s world would mean almost anyone.

This training course will be valuable to professionals, including (but not limited to) the following:

  • Technology Engineers
  • Chief Technology Officer (CTO)
  • Chief Information Officer (CIO)
  • Data Scientists
  • Data Analysts
  • Statisticians and Technology Personnel
  • Marketing and Research Specialists
  • Project Managers
  • Project Engineers
  • Supply Chain and Logistics Personnel
Daily Discussion


  • Introduction to Data Architecture
  • Data analytics importance
  • Data analytics use in modern industries
  • KDD process in Data Analytics
  • Introduction to CRoss Industry Standard Process (CRISP) – DataMining (DM)


  • Introduction to Descriptive Statistics
  • Importance of Data Visualisation
  • Multivariate Analytics
  • Use of Different Software (SPSS, SAS, R, Python, Statistica, and Excel)
  • Importance of open-minded Data Analytics


  • Issues in Data Quality
  • Clustering Analysis
  • Use of Regression
  • Predictive Methods
  • The overall importance of Data Analytics


  • Data Visualisation
  • Single Dimension, Two-Dimension and Multi-Dimension Data Visualisation
  • Histograms and other Charts
  • Charting within Excel, SPSS and SAS
  • Pareto Analysis


  • Linear, Exponential and Polynomial Regression
  • ANOVA (Analysis of Variance)
  • Fourier Transform
  • Theory of Probability
  • Confidence Limits