Business Research Analytics: Tableau

Running head: BUSINESS RESEARCH ANALYTICS: TABLEAU
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Business Research Analytics: Tableau
Student’s Name
Professor’s Name
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BUSINESS RESEARCH ANALYTICS: TABLEAU
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Business Research Analytics: Tableau
Part I
Visualization of Data
Tableau is a very interactive visual analytics platform that allows easy user-interface by
supporting drag and drop functionality when it comes to the presentation of data. As a result,
Tableau allows the researcher to make numerous alterations in the assessment criteria i.e.
changing x and y variables or sorting by color. Tableau allows for the provision of
comprehensive visual feedback that promotes the researcher to make sound and informs
conclusion. It is every easy for the data analyst to manipulate customer service figures from a
company like Vodafone New Zealand (Coe, et.al. 2017). The company analyst is able to assess
customer services based on region because the BI software supports world map data
representation format. As a result, the company is able to gather information on regions that
observed excellent and sub-standard customer service over the past financial year. Tableau is
preferred by many businesses because of the availability of numerous visual tools negating the
need to utilize numerous BI software to get all the necessary charts, tables, and regional maps.
Finally, Tableau has a dashboard visual presentation feature that allows for the presentation of
multiple visual tools in the same window as a way to draw cross tabulation and summarize
company dealings. Designing a dashboard is straight forward due to informative templates and
the useful drag and drop functionality. A company like Vodafone NZ (New Zealand) can
tabulate several items on a single dashboard to get a clear picture of the business’ performance in
terms of pricing, customer services, network coverage, value of money, and accessibility (Coe,
et.al. 2017). Below is an example of dashboard generated in tableau:

BUSINESS RESEARCH ANALYTICS: TABLEAU
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Segmentation and Cohort Analysis
In order for a business like Vodafone NZ to generate a plausible hypothesis about
company performance they need to first create data segments and carry out cohort analysis. The
data experts in the company can formulate several questions about different segments as a way
of understanding data and drawing conclusions on suitable hypothesis. For example, data experts
at Vodafone NZ can ask “How many teens utilize our services within the Auckland
metropolitan?”. Tableau allows data scientists to clearly visualize projects and create models that
will promote continued growth by highlight problem and success areas (Kamkolkar, et.al. 2014).