Employed.
Answers:
Dataset used in this visualization is about use of big data in enterprises, availability of data weather a enterprise is collecting enough data to make rational decisions based on that data, data related skill sets if enterprise have right employee like data scientist, machine learning engineers who can perform data related models to get insights out of data in order to support right decision making or data driven decision making, weather companies fit with data oriented approaches like Bayesian methods, statistical data analysis, exploratory data analysis and tool for analyzing data like power BI. Data analysis techniques used is coherent data analysis which examines the behaviors of different groups in our case groups are enterprises. Most of the data technique use is descriptive data analysis. (R. Toasa, 2018)
Answers:
Core story: Core story is about the use of data in decision making by cooperate sector or enterprise level companies and availability of right people to use data and availability of data to perform analysis. Visualization also describe that most of the almost 60% of the enterprises does not have the right process, technology stack and skilled employees to overall optimize the performance of the organization and make things less repetitive and innovative.
Report also describe the new generation of CEOs need the use of data and analytics techniques for effective and returning decisions.
After this visualization describe the ways to reduce the non-data oriented environment by conducting seminars, building cross functional teams in order to create awareness.
At last this describe the strong basis for data oriented decision making is collaboration, cooperation, problem solving. (R. Toasa, 2018)
Approach in this visualization is first an argument is provided then related stats or numbers are presented in order to support and clarify those arguments.
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Visualization is very descriptive instead of showing the original graphs descriptive results are mentioned, this report is good but the whole visualization is about this. No proper graphs showing percentages and numbers are presented in order to gain more deep understanding of the underlying problem and also for reading of advanced user there should be some charts like pie chart, bar chart etc.
In terms of usability this visualization is good because stats share are effective communicating what are the key steps and issues with current decision making approaches. In case of legibility stats shown in visualization under consideration are clear enough to convey their intent motive discussing what, why and how questions. (Hou, 2017)
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Improvement in visualization could be adding statically data analysis by adding, plots like bar charts, pie chart, line charts to show the deep in depth insights of data.
There should be use of new data mining, machine learning, coherent analysis, cluster analysis, retention analysis, predictive analysis to give future recommendations of how can cooperates and enterprises can leverage the new tools to improve their data driven decision making and how to adjust company culture to better understanding of process inside the company so that these process can be re-arranged or improve to get better understanding and get better return on investment. (S. M. Ali, 2016)
1. Purpose of the visualization under consideration is to preach awareness about importance of data in process making of enterprises. Also this visualization explains the current use of data and data analytics technique in different enterprises and showing the bad impact on ROI and processes due to those non data base decisions. The main goal of visualization was to share the facts about current use of big data and data analytics in decision making, how improvement can be done in this field along with benefits of doing so. (S. M. Ali, 2016)
2. Stakeholder for visualization under consideration are CEOs of new generation, enterprises, employees on enterprises use to of old company culture and not accepting new approaches, data scientist, other actors which can use data to perform better and get better return on investment.
3. Only visuals used in visualization under considerations are, 1 out of the enterprises use data & analytics in transformative way, 60% of the enterprises do not have right people, processes, technology to improve performance, the top new type of CEOs needs the most data and analytics workers among the tech-related skills. (R. Toasa, 2018)
4. Yes, this visualization describe the where improvement should be made to adopt data driven decision making like company strong culture, other competitors using similar approaches and what kind of skills and people needed.
5. Stakeholder can adopt to this approach also benefits and how the adopt data driven decision making is described in visualization.
6. Quality of visuals are normal, most of the visuals are descriptive.
Hou, Y. L. (2017). Methods and Techniques in Data Visualization Model. 2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC), (pp. 71-74). Dalian.
Toasa, M. M. (2018). Data visualization techniques for real-time information — A custom and dynamic dashboard for analyzing surveys' results. 13th Iberian Conference on Information Systems and Technologies (CISTI), (pp. 1-7). Cacere.
M. Ali, N. G. (2016). Big data visualization: Tools and challenges. 2nd International Conference on Contemporary Computing and Informatics (IC3I), (pp. 656-660). Noida.
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