Eurotech Training Consultancy Recruitment Fadi Jawad

Data Mining & Business Intelligence

Data Mining & Business Intelligence

Data Mining & Business Intelligence

 

INTRODUCTION 

Information is power. And information comes from data.

But with the massive amount of data that is available to all organisations today – from within the organisation’s information technology systems and from the outside through the Internet of Things (IoT) and Big Data sources – how do we turn that data into information?

Business intelligence is a collection of tools, techniques and approaches which includes data mining, data science, artificial intelligence, machine learning, neural networks, data visualisation, deep learning and others that identify the sources of data, discern patterns, associations, clusters and relationships in the data to turn data into meaningful information. That information can be used to produce the answers to big questions, diagnose and solve difficult or impossible problems, and even predict the future.

This highly interactive course explores the various forms and architecture of business intelligence and how business intelligence and its associated technologies are used to help organisations make operational and strategic decisions. The course introduces data mining, as it is used to support business intelligence through analysing vast amounts of data to produce information and recommendations by application of association rules, K-Nearest Neighbour (KNN) analysis, clustering, and Market Basket Analysis.

Participants will explore the various visualisation techniques that present the information in formats that help in decision making and predictions. Participants will also study some of the business intelligence and data mining tools, especially for visualisation of data and for predictive analytics.

 

OBJECTIVES 

By the end of the course the participants will be able to: 

  • Use data-based tools to make more accurate and timely decisions
  • Understand the mechanics and architecture behind business intelligence, data mining and Big Data
  • Utilise data mining techniques for predictive analysis, to assist in making decisions about the present and predicting future events
  • Visualise data using business intelligence and data mining visualisation methods and tools

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 OUTLINE

MODULE 1 – Analytics Overview
  • Business Analytics Overview, Trends, Case Studies
  • Understanding Business Intelligence and Analytics
MODULE 2 – Business Analytics Foundations
  • Introduction to Data Mining CRISP-DM
MODULE 3 – Predictive Analytics Modeler
  • Nodes and streams
  • Initial data mining, storage and field measurement
  • Understanding the data (valid and invalid values)
  • Integrating data (methods, options, merging, and sampling)
  • Deriving and reclassifying fields (CLEM)
  • Looking for relationships (matrix, distribution, means, histogram, statistics and plot)
  • Functions (conversion, string, and statistical)
  • Statistical, graphical and sample nodes
  • Automated data mining and modelling
  • Predictive models and customer segmentation

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