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Fundamentals of Business Analytics Training Course

Formats ⟩  Live Virtual: 4 hrs./day, 2 Days  |  In-Person: 6 hrs./day, 2 Days

In today's fast-paced business environment, effectively harnessing and interpreting data is crucial. Whether starting in analytics and business intelligence or simply looking to brush up on specific areas, this two-day business analytics course is structured to enhance your knowledge and provide actionable insights, empowering you to effectively employ analytics in your work.

Course Prerequisite: Introduction to Data Analytics

Recommended Follow-Up: Introduction to Data Literacy

Learning Objectives »

  • Understand the role and importance of data in modern businesses.
  • Distinguish between data, information, and knowledge.
  • Identify different types of data and their sources.
  • Learn methods for data collection, storage, and management.
  • Understand various business analysis types and their uses.
  • Master key analytical techniques and models.
  • Explore tools for data analysis and visualization.

Course Agenda

Business Analytics Intro.

  1. What Are Business Analytics?
  2. The Significance and Evolution
  3. Implementing Business Analytics
  4. Skills and Resources Needed To Excel

Common Analytic Methods

  1. Agile Perspective
  2. Business Intelligence (BI)
  3. Information Technology (IT)
  4. Business Analysis (BA)
  5. Business Process Management (BPM)

Types of Business Analytics

  1. Descriptive Analytics: Evaluating What
  2. Diagnostic Analytics: Understanding Why
  3. Predictive Analytics: Forecasting When
  4. Prescriptive Analytics: Guiding Decisions

Analytical Framework

  1. SWOT
  2. PESTLE
  3. Gap Analysis
  4. Porters Five Forces
  5. Value Chain Analysis
  6. Ansoff’s Matrix
  7. Balanced Scorecard

Business Analytic Tools

  1. Data Collection and Storage
  2. Processing and Management
  3. Basic and Advanced Analytical
  4. Data Visualization and Reporting

Predictive Analysis and Forecasting

  1. The Role of Predictive Forecasting
  2. Common Tools and Techniques
  3. Regression Analysis
  4. Time Series Analysis
  5. Clustering And Classification

Strategic Business Analytics

  1. Aligning Analytics with Objectives
  2. Data-Driven Decision Making
  3. Data-Informed Decision Making
  4. Common Implementation Challenges

Future Trends in Business Analytics

  1. Artificial Intelligence (AI)
  2. Machine Learning (ML)
  3. Augmented Analytics
  4. Big Data Analytics
  5. Data as a Service (DaaS)
  6. Ethical Considerations in Data
Close up business people meeting to analyze data captured and understanding it.

Fundamentals of Business Analytics Training Course

Formats ⟩  Live Virtual: 4 hrs./day, 2 Days  |  In-Person: 6 hrs./day, 2 Days

In today's fast-paced business environment, effectively harnessing and interpreting data is crucial. Whether starting in analytics and business intelligence or simply looking to brush up on specific areas, this two-day business analytics course is structured to enhance your knowledge and provide actionable insights, empowering you to effectively employ analytics in your work.

Course Prerequisite: Introduction to Data Analytics

Recommended Follow-Up: Introduction to Data Literacy

Learning Objectives »

  • Understand the role and importance of data in modern businesses.
  • Distinguish between data, information, and knowledge.
  • Identify different types of data and their sources.
  • Learn methods for data collection, storage, and management.
  • Understand various business analysis types and their uses.
  • Master key analytical techniques and models.
  • Explore tools for data analysis and visualization.

Course Agenda

Business Analytics Intro.

  1. What Are Business Analytics?
  2. The Significance and Evolution
  3. Implementing Business Analytics
  4. Skills and Resources Needed To Excel

Common Analytic Methods

  1. Agile Perspective
  2. Business Intelligence (BI)
  3. Information Technology (IT)
  4. Business Analysis (BA)
  5. Business Process Management (BPM)

Types of Business Analytics

  1. Descriptive Analytics: Evaluating What
  2. Diagnostic Analytics: Understanding Why
  3. Predictive Analytics: Forecasting When
  4. Prescriptive Analytics: Guiding Decisions

Analytical Framework

  1. SWOT
  2. PESTLE
  3. Gap Analysis
  4. Porters Five Forces
  5. Value Chain Analysis
  6. Ansoff’s Matrix
  7. Balanced Scorecard

Business Analytic Tools

  1. Data Collection and Storage
  2. Processing and Management
  3. Basic and Advanced Analytical
  4. Data Visualization and Reporting

Predictive Analysis and Forecasting

  1. The Role of Predictive Forecasting
  2. Common Tools and Techniques
  3. Regression Analysis
  4. Time Series Analysis
  5. Clustering And Classification

Strategic Business Analytics

  1. Aligning Analytics with Objectives
  2. Data-Driven Decision Making
  3. Data-Informed Decision Making
  4. Common Implementation Challenges

Future Trends in Business Analytics

  1. Artificial Intelligence (AI)
  2. Machine Learning (ML)
  3. Augmented Analytics
  4. Big Data Analytics
  5. Data as a Service (DaaS)
  6. Ethical Considerations in Data
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