Data Mining and Management Strategies

Course Info

Length:

10 Days

Type:

In Classroom

Available Dates

2025-04-28

Dubai

2025-05-26

London

2025-05-26

Amsterdam

2025-05-26

Barcelona

2025-05-26

Singapore

2025-05-26

Paris

2025-05-26

Kuala Lumpur

2025-05-26

Istanbul

2025-06-16

Dubai

2025-07-28

London

2025-08-25

Kuala Lumpur

2025-08-25

Amsterdam

2025-08-25

Barcelona

2025-08-25

Paris

2025-08-25

Istanbul

2025-08-25

Singapore

2025-08-25

Dubai

2025-09-15

London

2025-10-27

Dubai

2025-11-24

Kuala Lumpur

2025-11-24

Singapore

2025-11-24

Istanbul

2025-11-24

Paris

2025-11-24

London

2025-11-24

Barcelona

2025-11-24

Amsterdam

2025-12-15

Dubai

Course Details

  • Introduction
  • Objective
  • Who should attend

 

Data Mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. Data mining tools allow enterprises to predict future trends.

 

Data Mining has great importance in today’s highly competitive business environment. Data mining is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, e-commerce, investment trend in stocks & real estates, telecommunications, and so on. Data Mining is based on mathematical algorithms and analytical skills to drive the desired results from the huge database collection.

 

Data Mining and Management Strategies training course will help you uncover and explore hidden patterns in the data, providing insight to predict, experiment, and continuously refine strategic decisions with big business impact. You will explore marketing business processes that increasingly rely on analytics, including customer acquisition, marketing segmentation, and understanding customer lifetime value. Use analytical tools to develop models to support these business processes.

Course Outline

10 days course
  • Day 1
  • Day 2
  • Day 3
  • Day 4
  • Day 5
  • Day 6
  • Day 7
  • Day 8
  • Day 9
  • Day 10
 
Enterprise Database and Data Models
 
  • Key differences between data and information.
  • An understanding of enterprise database environments.
  • Define specific challenges with data cleansing.
  • The elements that make up a data model.
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