Fair Business Decisions - Data in Business

Understanding Business Tasks in Data Analytics

  • Business Tasks: The central questions or problems that data analysis aims to address for businesses.

Core Concepts

  • Issues: Topics or subjects that need investigation.

  • Questions: Designed to uncover specific information regarding an issue.

  • Problems: Obstacles or complications requiring solutions.

Examples of Business Tasks

  • Coca-Cola: Question about new product flavors.

    • Data analysis provided insights into flavors customers already enjoy.

  • City Zoo and Aquarium: Problem with staffing.

    • Data analysis assisted in developing optimal staffing strategies based on visitor patterns.

Business Task Framework

  • Every business task. Begins with an issue, question, or problem that needs resolution.

  • Zoo Staffing Example:

    • Identified problem: Unpredictable weather affecting staffing needs.

    • Proposed business task: Analyze past weather data to find predictable patterns that inform staffing decisions.

Data-Driven Decision Making

  • Definition: Using facts obtained through data analysis to guide business strategies.

  • Decision making involves choosing between various consequences resulting from choices made.

  • Importance of data:

    • Enables informed decisions, improving outcomes over reliance on observation and memory.

    • Strength of Data: Provides a comprehensive view of problems and their underlying causes, facilitating innovative solutions.

Role of Data Analysts

  • With training, data analysts will learn to:

    • Formulate pertinent questions to address business tasks.

    • Develop strategies for collecting, analyzing, and presenting data effectively.

    • Create visual representations of data to support informed decision-making efforts.

  • As a data analyst, one is crucial to the success of any business due to the ability to leverage data effectively.

Responsibilities of Data Analysts

  • Next topic to explore: ethical responsibilities in data collection, analysis, and presentation in a fair manner.

  • Essential to ensure that the data represents all parties accurately, maintaining fairness and integrity in data analytics.