Back to course 'BUS612: Data-Driven Communications'

Topic outline

  • Unit 1: Defining the Business Objective and Sourcing Data

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    Before performing any analysis, there must be a clear business purpose for the analysis and an understanding of how the data will be collected, cleaned, and made available. This is often referred to as the extract, transform, load (ETL) operation, which is the general procedure of copying data from one or more sources into a destination system that may structure the data differently from the source or in a different context than the source. Uniformity in the final data structure helps minimize the chance for errors that could occur from using disparate data sources. It is just as important to understand the source of the data, utilize proper data gathering methodologies and organize the data into a consistent format as it is to actually perform the analysis. Without these prior steps, you could communicate incorrect results to the audience or fail to meet the business objective. In this unit, you will learn about defining clear data analysis objectives, identifying best practices in collecting or gathering data to support the objective, and utilizing proper verification techniques to ensure the validity of collected data.

    Completing this unit should take you approximately 6 hours.

    • Upon successful completion of this unit, you will be able to:

      • identify and define data analysis processes;
      • apply data analysis processes;
      • examine effective business analysis objectives;
      • create effective business analysis objectives;
      • evaluate effective business analysis objectives;
      • compare and contrast the different data gathering methods and models; and
      • illustrate how data collection impacts the final analysis.

    • 1.1: Data Analysis Processes

      Data-driven decision-making is collecting data, extracting patterns and facts from that data, and using those facts to guide decisions. Watch this video to explore how data is used to make decisions and the importance of using intuition as part of the process. Pay attention to the four-step method that guides data-driven decision-making, and think about how the author used data to drive decisions that improved his business outcomes.
       
      The four-step method is:

      1.  Have a clear objective.
      2.  Have a measurable outcome.
      3.  Make decisions based on current data.
      4.  Validate the outcome.

      How does using this method help create business opportunities and reveal new business insights?

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        Lifecycle of a Data Analysis Project Page
        Students must
        Mark as done

        Communication of analysis results with visualizations is a key component of the Data Analysis Lifecycle. Each step in the lifecycle must be performed correctly for the visualizations to have meaning and lead to good decisions. Understanding the steps that lead to creating visualizations is critical to the project's success. Watch this video to learn the 6-step process and its role in its success.

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        The Market Research Process Page
        Students must
        Mark as done

        Market research is a discipline that relies on an analysis process to communicate the results of its various types of research. Read this article to explore how the market research process is executed and how the reporting function is structured.

    • 1.2: Data Analysis Business Objectives

      • book icon
        Big Data Stream Analytics for Sentiment Analysis Book
        Students must
        Mark as done

        Big Data gives organizations unprecedented opportunities to tap into their data to mine valuable business intelligence. Read this study to learn how businesses can utilize this analytics framework to analyze consumers' product preferences, leading to more effective marketing and production strategies.

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        Data Modeling and Data Analytics Book
        Students must
        Mark as done

        Analyzing Big Data can create significant advantages for an organization because it enables the discovery of patterns and correlations in datasets. This paper discusses the state of Big Data management with a particular focus on data modeling and data analytics.

    • 1.3: Data Collection and Gathering Best Practices

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        Using BI and Decision-Making Process in Start-ups Book
        Students must
        Mark as done

        Read this article on how start-up companies use business intelligence systems to make decisions. It presents the objectives of using business intelligence, what companies need to use it successfully, and its applications in a start-up, beginning the data collection/gathering and ending with data presentation.

    • Unit 1 Study Resources

      This review video is an excellent way to review what you've learned so far and is presented by one of the professors who created the course.

      • page icon
        Unit 1 Review Video Page

        Watch this as you work through the unit and prepare to take the final exam.

      • resource icon
        Unit 1 Review Slides File

        You can also download the presentation slides so you can make notes.

      • url icon
        Study Guide: Unit 1 URL

        We also recommend that you review this Study Guide before taking the Unit 1 Assessment.

    • Unit 1 Assessment

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        Unit 1 Assessment Quiz
        Students must
        Receive a grade

        Take this assessment to see how well you understood this unit.

        • This assessment does not count towards your grade. It is just for practice!
        • You will see the correct answers when you submit your answers. Use this to help you study for the final exam!
        • You can take this assessment as many times as you want, whenever you want.