Course Overview

The Business Analytics Course is designed to equip learners with the skills and techniques needed to analyse business data, derive actionable insights, and make data-driven decisions. Participants will explore data analysis tools, predictive modelling, data visualisation, and statistical techniques. The course also covers the use of analytics in various business functions such as marketing, finance, and operations. By the end of the course, learners will be able to apply business analytics to solve real-world problems and drive organisational performance

 

Prerequisites

A basic understanding of business concepts is recommended. Familiarity with data analysis tools such as Excel or Google Sheets is an advantage but not required.

Target Audience

This course is ideal for business professionals, managers, analysts, and individuals who want to enhance their ability to make data-driven decisions. It is also suitable for individuals looking to gain practical skills in business analytics and data analysis.

Course Highlights

  • Learn key business analytics concepts and data analysis techniques.
  • Develop skills in using data analysis tools like Excel, Power BI, and SQL.
  • Explore predictive modelling and statistical analysis to forecast trends.
  • Gain hands-on experience in analysing business data to derive insights.
  • Understand how to apply business analytics to marketing, finance, and operations.

Course Objectives

By the end of this course, learners will be able to:

  • Apply business analytics tools and techniques to analyse data and derive insights.
  • Collect, clean, and prepare data from multiple sources for analysis.
  • Use data visualisation tools to communicate insights effectively to stakeholders.
  • Build predictive models to forecast business trends and outcomes.
  • Implement data-driven decision-making in marketing, finance, operations, and other business functions.
  • Leverage SQL, Excel, and Power BI to perform data analysis and create dashboards.
  • Evaluate the accuracy and effectiveness of predictive models and analytics solutions.
  • Use business analytics to optimise business operations and improve organisational performance.
  • Apply descriptive, predictive, and prescriptive analytics to solve business problems.
  • Present data insights in a clear and actionable manner to support business strategies.

 

Course Outline

Instructional Methods: Group discussions on the importance of analytics, practical exercises in data collection, and case studies on how businesses use analytics.

Topics Covered:

  • Understanding business analytics: Key concepts and applications.
  • The role of data in driving business decisions.
  • Types of business analytics: Descriptive, predictive, and prescriptive.
  • Data sources: Internal vs. external data.
  • Challenges and opportunities in business analytics.

Instructional Methods: Hands-on exercises in data collection, group discussions on data preparation techniques, and case studies on preparing data for analysis.

Topics Covered:

  • Methods of data collection: Surveys, transaction data, and web data.
  • Cleaning and preparing data for analysis.
  • Handling missing and inconsistent data.
  • Data integration from multiple sources.
  • Using data warehouses and databases for analytics.

Instructional Methods: Practical exercises in using tools like Excel, SQL, and Power BI, group discussions on analysis techniques, and case studies on data-driven decision-making.

Topics Covered:

  • Overview of business analytics tools: Excel, SQL, Power BI, and Tableau.
  • Descriptive analytics: Summarising and interpreting business data.
  • Using SQL for querying databases and retrieving data.
  • Data visualisation techniques for effective communication of insights.
  • Advanced Excel techniques for data manipulation and analysis.

Instructional Methods: Hands-on exercises in building predictive models, group discussions on forecasting techniques, and case studies on predicting business outcomes.

Topics Covered:

  • Predictive analytics: Understanding patterns in data.
  • Building regression models for forecasting.
  • Time-series analysis for predicting trends.
  • Using machine learning models for business forecasting.
  • Evaluating the accuracy and reliability of predictive models.

Instructional Methods: Group discussions on using analytics in business functions, practical exercises in applying analytics to real-world problems, and case studies on marketing, finance, and operations analytics.

Topics Covered:

  • Marketing analytics: Customer segmentation, churn prediction, and campaign analysis.
  • Financial analytics: Forecasting revenue, managing risk, and budgeting.
  • Operations analytics: Optimising supply chain, inventory management, and process efficiency.
  • Human resource analytics: Workforce planning and performance evaluation.
  •  Integrating business analytics across different functions for organisational success.

Instructional Methods: Practical exercises in creating dashboards, group discussions on effective visualisation, and case studies on communicating data insights to stakeholders.

Topics Covered:

  • Data visualisation principles: Telling a story with data.
  • Creating dashboards with Power BI and Tableau.
  • Presenting data insights to non-technical stakeholders.
  • Choosing the right charts and graphs for different data types.
  • Best practices for communicating data-driven insights clearly and effectively.

Certification

A certificate of completion will be awarded upon successful completion of the course.

Course Fees

$788 $488

Business Analytics

Enhance Marketing, Finance, and Operations with Analytics

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Enhance Marketing, Finance, and Operations with Analytics

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