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Data Analytics Fundamentals Training Series

Formats ⟩  Live Virtual: 4 hrs./day, 5 Days  |  In-Person: 6 hrs./day, 5 Days

This 5-day data discovery series combines our data analytics foundation courses—Introduction to Data Analytics, Introduction to Business Analytics, and Introduction to Data Literacy—into a broad range overview of analytics and its implications in today’s business world. You will learn how to apply data analytics principles in your organization, actionable insights for business analytics, the essence of data literacy, and how each profoundly impacts business decision-making.

Learning Objectives »

  • Examine the fundamental concepts of data analytics, business analytics, and data literacy.
  • Understand the impact of analytics on organizational strategy and operations.
  • Learn to solve analytical problems.
  •  Identify different types of data and their sources.
  • Explore tools for data analysis and visualization.
  • Make effective business decisions and improve ROI using analytics.
  • Master key analytical techniques and models.
  • Identify key concepts in data literacy.
  • Develop skills in data interpretation and visualization.
  • Identify upcoming trends in analytics.

Course Agenda

Intro. to Data Analytics (2-Days)

  1. Importance of Data Analytics
  2. Types of Data and Data Analytics
  3. Data Visualization
  4. Data Science and Machine Learning
  5. Analytics Framework and Latest Trends

Intro. to Business Analytics (2-Days)

  1. Understanding Business Analytics
  2. Common Analytic Methods
  3. Types of Business Analytics
  4. Analytical Frameworks
  5. Business Analytics Tools
  6. Predictive Analysis and Forecasting
  7. Strategic Business Analytics
  8. Future Trends in Business Analytics

Intro. to Data Literacy (1-Day)

  1. Defining Data Literacy
  2. Basic Concepts of Data Literacy
  3. Data, Information, and Knowledge
  4. Types and Sources of Data
  5. Data Interpretation Techniques
  6. Integrating Data with Strategy
  7. Frameworks and Techniques
  8. The Road Ahead for Data Literacy
A group of business professionals meeting at a table reviewing data analytic information and graphs.

Data Analytics Fundamentals Training Series

Formats ⟩  Live Virtual: 4 hrs./day, 5 Days  |  In-Person: 6 hrs./day, 5 Days

This 5-day data discovery series combines our data analytics foundation courses—Introduction to Data Analytics, Introduction to Business Analytics, and Introduction to Data Literacy—into a broad range overview of analytics and its implications in today’s business world. You will learn how to apply data analytics principles in your organization, actionable insights for business analytics, the essence of data literacy, and how each profoundly impacts business decision-making.

Learning Objectives »

  • Examine the fundamental concepts of data analytics, business analytics, and data literacy.
  • Understand the impact of analytics on organizational strategy and operations.
  • Learn to solve analytical problems.
  •  Identify different types of data and their sources.
  • Explore tools for data analysis and visualization.
  • Make effective business decisions and improve ROI using analytics.
  • Master key analytical techniques and models.
  • Identify key concepts in data literacy.
  • Develop skills in data interpretation and visualization.
  • Identify upcoming trends in analytics.

Course Agenda

Intro. to Data Analytics (2-Days)

  1. Importance of Data Analytics
  2. Types of Data and Data Analytics
  3. Data Visualization
  4. Data Science and Machine Learning
  5. Analytics Framework and Latest Trends

Intro. to Business Analytics (2-Days)

  1. Understanding Business Analytics
  2. Common Analytic Methods
  3. Types of Business Analytics
  4. Analytical Frameworks
  5. Business Analytics Tools
  6. Predictive Analysis and Forecasting
  7. Strategic Business Analytics
  8. Future Trends in Business Analytics

Intro. to Data Literacy (1-Day)

  1. Defining Data Literacy
  2. Basic Concepts of Data Literacy
  3. Data, Information, and Knowledge
  4. Types and Sources of Data
  5. Data Interpretation Techniques
  6. Integrating Data with Strategy
  7. Frameworks and Techniques
  8. The Road Ahead for Data Literacy
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