Boost
Boost

AI-Powered Data Analysis for Business

AI-3885

Course Code

5 Days

Duration

4

Upcoming Dates

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Sector Name

Artificial Intelligence (AI)

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21 Dec 2026 | 25 Dec 2026
Abu Dhabi, UAE
$4,250
Limited Seats
25 Jan 2027 | 29 Jan 2027
Dubai, UAE
$4,250
Upcoming
20 Jun 2027 | 24 Jun 2027
Riyadh, KSA
$4,250
Upcoming
30 Aug 2027 | 03 Sept 2027
Lausanne, Switzerland
$5,950
Upcoming

Course Introduction

Business professionals increasingly work with data but often face a gap between having information and being able to extract useful meaning from it. Artificial intelligence can make data exploration and analysis more accessible by helping users formulate analytical questions, examine patterns, compare performance, identify anomalies, and explain findings. However, fluent AI-generated explanations can also create false confidence when calculations, assumptions, or interpretations are not properly verified.
 

Boost Consulting & Training offers this course to develop practical capability in using AI throughout the business data analysis journey. Participants learn to translate business questions into analytical tasks, prepare and explore data, use AI to support analysis, investigate patterns and performance drivers, validate AI-generated interpretations, visualize findings, and communicate business meaning. The course focuses on analytical thinking and business applications rather than programming or advanced data science.
 

The main concept of this course is to combine AI-assisted analysis with human analytical judgement so that business data can be explored faster without sacrificing the accuracy and credibility of the conclusions drawn from it.

Course Objectives

  • Translate business questions into clear data analysis requirements.
  • Assess and prepare business data before using AI-assisted analysis.
  • Use AI to explore datasets and generate relevant analytical questions.
  • Identify trends, patterns, anomalies, and performance differences in business data.
  • Investigate possible drivers behind observed results.
  • Validate AI-generated calculations, interpretations, and analytical conclusions.
  • Develop clear visual and narrative explanations of analytical findings.
  • Convert validated data insights into meaningful business implications.
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