BUS610: Business Intelligence and Analytics

6a. Examine visualization best practices for different audiences 

• How do visualizations make large amounts of data easier to understand?
• How do visualizations reveal data at several levels of detail, from a broad overview to a fine structure?
  

Well-crafted data visualizations not only present data in easily understood images but when done well, they enable the viewer to quickly perceive insights they may have missed if presented in summary tables and spreadsheets. Good data visualization does not only convert large amounts of data into images, but when done well, it engages the viewer and tells a story.
 
Well-crafted visualizations present complex ideas or results and communicate them with clarity, precision, and efficiency. Visualizations should:

• show the data;
• have the viewer on the substance instead of the methodology;
• avoid distorting the data;
• present many numbers in a small space;
• make large data sets easier to understand; and
• present the data at several levels of detail, from a high-level overview to a deep data dive.
  

With the advent of better software, faster processors, and cheaper memory, it has become easier to create and iterate visualizations. With this power comes responsibility, as it is crucial to building good visualizations that clearly articulate the analyst's point. Visualizations can be effective or ineffective, generating very strong feelings either way.
 
Data visualizations are useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. It is essential for exploratory data analysis and data mining to check data quality and improve an analyst's familiarity with the structure and features of the data before them.
 
Presentation graphics are usually a select number of graphics created for any number of people and need to be well-designed and well-created with an effective explanatory text, either verbally or textually. They are used to convey known or summarized information.
 
Exploratory graphics can include several graphics created for an individual such as yourself. They don't need to be perfect but provide alternate views and additional information.
 
To review, see The Beauty of Data Visualization.
 

6b. Explain the increasing ways in which human decision-making is converging with artificial intelligence to improve both 

• How is OLAP used to conduct BI analysis?
• How are emerging AI technologies being used and converging with human decision-making?
  

The business sector developed Online Analytical Processing technology (OLAP) to conduct business intelligence analysis and look for insights. An OLAP data cube is a multidimensional array of data. A data cube is designed to organize data by grouping it into different dimensions, indexing the data, and precomputing queries frequently. It is important to understand the operations we can perform on a data cube and apply them correctly to the problem under consideration. OLAP systems allow flexible and dynamic questions to be asked of big data. Combining OLAP with the techniques of multicriteria decision-making allows business executives to incorporate insights from real-world data into the systematic evaluation of different business options. This improves the quality of complex decisions and leads to better business outcomes with the same resources.
 
In the age of big data and artificial intelligence, there are several unintended risks and potential malicious uses of the technology. Every organization needs to adopt a set of data governance standard operating procedures. They are opening themselves up to unnecessary litigation and a negative reputation without such.
 
The primary objective of a weak AI is to emulate human mental faculties through the use of models implemented on a computer. Notice that the focus is on the output, not the process. We are trying to achieve a result similar to what a human would have achieved. We are not trying to model or duplicate the cognitive process that humans used. The objective of a weak AI system is not to embody human capabilities, which would imply that the AI "thinks" in the same manner as a human; it is to emulate them on a computer through models. The main focus of a weak AI is on the output, not the cognitive process. In particular, emotions are poorly understood, even in humans, and machines are not, at present, capable of modeling or emulating them.
 
We use models that attempt to emulate the results of human cognition on a computer, but we cannot model many aspects of human cognition. In particular, emotions are poorly understood, even in humans, and machines are not, at present, capable of modeling or emulating them.
 
For the full benefits of technological advances to be gained in society, a collaborative approach to machines and humans working together must continue to be paramount. For generations, humans and machines have worked together. Why would it stop now? Humans will continue to offer creativity, social skills, and qualitative aspects to the partnership. Machines will bring quantitative aspects, speed, and the ability to scale rapidly. The nuances of language, such as the ability to joke, still remain outside of the grasp of machines, while quantum computing is nearly impossible for humans. By combining forces, true innovation is bound to happen.
 
As AI capabilities and ubiquity are extended, humans will need to learn how to work with it and ensure that its influence on human well-being is positive. We will need to ensure that human judgment maintains its primacy and that we are up to the task. There will be immense economic pressure to adopt AI. We must train a new generation of both data scientists and data science users who can guide this adoption to the benefit of humankind.
 
To review, see Artificial Intelligence and the Future of Humans.
 

6c. Describe the critical elements of reporting that clearly communicates analytic estimates to decision-makers 

• How are data visualizations used to communicate information to decision-makers?
• How can we effectively communicate via memoranda and other written forms?
  

Mass communication takes many forms in business. Memoranda and letters are two generally used in an official capacity. How your reports are written, including content, form, beautiful aesthetic data visualization presentations, and utilizing a framework such as the SMART model to showcase your goal setting with robust data will set you apart.
 
Visualizations are a tool to help the audience better understand large data sets. They should not be distracting or distorting the data and help the viewer focus on the substance rather than the methodology.
 
Good data visualization uses different visual characteristics (color, size, orientation, etc.) to encode information effectively at higher densities than would be possible in a plain text version. It is essential to test your visualizations with real users during the development process. This testing should focus on measuring the expressiveness and effectiveness of the presentation. Write in your journal about how people with a visual impairment might be included in the development process. A good visualization is a piece of data art composed to achieve a purpose. Whenever somebody looks at your visualization, you want them to reach the same conclusion as you, and they should be able to do so without having to dissect the information.
 
During data analysis, some helpful tips to keep in mind include:

1. Communicate all of the results
2. Try to avoid bias when interpreting data
3. Failure to confirm the original hypotheses does not mean the research results are useless
   

Reducing the need for the audience to interpret the findings in visualization is the key to an effective presentation. This can be accomplished by the type of chart used or by highlighting key points through color choices.
 
Storytelling has been a useful tool to communicate information and knowledge over time. Using visualizations to tell a story with data helps make the information more concise and memorable. The most effective storytelling helps the audience reach the right conclusion and take the appropriate action.
 
To review, see Memorandums and Business Letters.
 

Unit 6 Vocabulary 

This vocabulary list includes the terms that you will need to know to successfully complete the final exam.

• artificial Intelligence (AI)
• data cube
• clarity
• efficiency
• exploratory graphics
• linear storytelling
• online analytical processing (OLAP)
• precision
• presentation graphics
• random access storytelling
• user-directed path storytelling
• visualization
• weak AI