In chapter, Mr. Kirk explains about the workflow and path of visually analyzing data, the visualization workflow is a key concept in implementing a data visualization tool in an enterprise and the chapter benefits the reader with typical representations of the concept in mutual combination of theoretical definitions. The conceptual workflow involves around the decision forensics, assessment of the current workflow and a final analysis of potential problems.
The decision forensics speaks about sample visualization and forensically decipher the designs and pattern of data and deconstruct a puzzle to get to the root of the theme under consideration. The tactics involved is explained and the need to find hidden contexts and behind the scenes data is important. The stage of current workflow talks of the existing setup. Advantages, disadvantages, need to improve and the benefits of improved visualization analysis.
the author emphasizes an activity involving brainstorming the reader to perform data gathering, ideas to implement a project plan with the manager at an enterprise and to learn the underlying concept of data visualization. This provided a learning opportunity to the reader to engage in the book and analyze their situation based on this concept.
Ideas and thoughts:
The author presents us a unique way of representing data visualization through workflow models that can highly impact the decision maker to choose a path that can be totally different to the existing setup.
Upon reading the chapter 2, I was able to gather info about the use of data gathering and arrangement before processing. A quick thought on this provided the possibility of segregating data beforehand in order make the process smooth and to eliminate unusable data. This can save a lot of time and money when the size of data is large. A further benefit was to improvise the existing setup by going through the existing setup and acquire hidden data. However, this needs to be done without unintended downtime and loss to an organization.
The workflow can be implemented in my current personal space while assessing the amount of data stored in my emails coming from credit card transactions. Upon logging into my credit card activity statement, I can filter thrones that are needed. This can help benefit me to keep track of the required ones and delete the rest of junk. Nowadays, since this is visually available through graphs, it makes life easier to organize the data before acting.
Meanwhile, in an enterprise, the importance of workflow cannot be emphasized enough. The need to gather historical data is quintessential in terms of auditing and cost analysis. The most important part is the effect this has in future decision-making processes.
The next application is to perform thorough research on the hidden data that can go missing but can have a significant impact on the outcome of a project. For example, if the data usage over a weekend is not captured as it was a long weekend, it affects the next part of the report and can mislead a user to perform wrong analysis.