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3 - 5 November 2025
In Person or Live Digital

Attendees

WHO SHOULD ATTEND

This course is designed for Managers, Executives, Data Scientists, Data Analysts, Business Analysts, professionals working with data analytics or business intelligence, and anyone who needs to understand how to use data to make better decisions.

COURSE REQUIREMENTS AND CERTIFICATES

Delegates must meet two criteria to be eligible for an Informa Certificate of Completion for a course:

  1. Satisfactory attendance – delegates must attend all sessions of the course. Delegates who miss more than 2 hours of the course sessions will not be eligible to sit the course exam
  2. Successful completion of the course assessment.

Delegates who do not meet these criteria will receive an Informa Certificate of Attendance. If delegates have not attended all sessions, the Certificate will clearly state the number of hours attended.

COURSE PREREQUISITES

Delegates are required to have a basic understanding of information technologies and statistics.

COMPETENCIES

Understanding business intelligence

Performing online analytical processing

Investigating the Extraction, Transformation, Load (ETL) process

Understanding data analytics

Understanding data mining

Exploring Cross-Industry Standard Process for Data Mining (CRISP-DM)

Implementing predictive analytics

Using cluster analysis

Exploring data mining models

Creating association rules

Using data visualisation methodologies

Managing data dashboards

COURSE METHODOLOGY


This highly interactive course employs the latest in business intelligence and data mining technologies. In addition to practical exercises with business intelligence graphics and data mining algorithms, participants will see real-life business examples of business intelligence and data mining in use with an emphasis on predictive analytics.

Participants will learn how to form questions and develop analytics techniques which are then transformed into business intelligence. Participants will also practice the statistical techniques behind data mining and producing recommendations for and predictions about the business. Additionally, participants will learn how to apply artificial intelligence, neural networks, and machine learning to the application of business intelligence and data mining.

The course is primarily focused on doing rather than listening, so participants will be engaged in exercises for nearly 70% of the class time.