Reflection on Tableau Software

Tableau is a data visualisation tool that helps people to see and understand the forms of data. The tool meets the requirements of humanity data as it transforms peoples’ understanding and use of the data in solving problems. The tableau software converts raw data into a simple format that is easily understood. Data analysis is an important tool in industries related to business intelligence, and the in data visualisation. It creates an easy data that allows even non-technical users to customise the dashboard (Keller, 2016). The tool is interactive in data visualisation and it helps organisations to solve data problems. The features of the tableau software tool are; toggle view and drag-and-drop, dashboard commenting, tableau reader for data viewing, import of all ranges and sizes of data, translating queries to visualization, tableau public for data sharing, create interactive dashboard, share dashboards, highlight and filter data, automatic updates, data notification, and security permission at any level. Tableau provides receptive pricing in business with on-premise and cloud-hosted editions which are paid annually.

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The tableau software has the tableau desktop, tableau server, and tableau reader, tableau public, and tableau online. The tableau desktop is an application for data visualisation that analyses virtual structural data to produce interactive data on the dashboard. The tableau server is a solution to business intelligence that provides server-based visual analytics. The tableau reader is an application that allows users to read and interact with the dashboard created by the tableau desktop (Stirrup et al., 2016). The characteristics of the humanity data that can be used by tableau software for visualisation are; it should be scalable, accessible, give the right information, and enable rapid deployment and development. The limitations on the tableau software in application of data visualisation with the above features are; poor version support, security issues, and improper IT assistance on the software application.

The tableau software generates data that can be read free on the tableau reader after the data visualisation as the data output. The kind of data output from the software are interactive charts, dashboards, and reports useful in analysis. The tableau gives data displays in picture-perfect, interactive visual tables, graphic encoding, and side by side data comparison. The output is also interactive as users can easily understand without any programming or training. The limitations of the tableau software on the data output generated are; poor best-in-class capability, poor capability to allow smooth embedment of the data, and failure of the software to dynamically filter the data in the dashboard. The data can be shared through the dashboard for publication in the tableau server tool for viewing. The tableau has hidden assumptions on nature of knowledge of the data. These are quantities, entities, identities, and temporality. The assumptions carry on explicit knowledge as certain and observer-independent rather than interpretative and observer co-dependent (Drucker, n.d).

Tableau Software has become the best tool in data visualisation and business intelligence in the market. The best of the tool is that its power tool that does not require programming skills and allows access to reliable support team (Loth, 2019). The tableau software can be applied in digital humanist work on data visualisation. The hypothetical example where the tableau software is in managing business company operation since it has the capability of handling humanity data and providing analytical results. The software can also connect to multiple data source to improve on the performance in the unified informative dashboard. The operation of the company can be managed by the software since its ease to easy and can visualise any data in the company based on business intelligence.

 

References

Drucker, J. (n.d.). DHQ: Digital Humanities Quarterly: Humanities Approaches to Graphical Display. Retrieved November 24, 2019, from http://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html

Keller, L. (2016). Tableau Training Manual Version 10.0 Basic: From Clutter to Clarity. VIA Insights, LLC.

Loth, A. (2019). Visual Analytics with Tableau. Hoboken: Wiley.

Stirrup, J., Nandeshwar, A., Ohmann, A., & Floyd, M. (2016). Tableau: Creating Interactive Data Visualizations. Birmingham: Packt Publishing.