Building Trust In Analytics

Two Discussions

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Discussion #1 Original Post

Review the video above and using peer reviewed articles found in the library to back up your position, discuss why trust in the data is important.  As part of your discussion discuss the 4 anchors mentioned in the video and their relationship to evaluating risk associated with the data.  Be sure to provide specific examples to support your position.

 

 

Building Trust in Analytics Video Summary

 

We’re using more and more algorithms in our daily lives

 

· 77% of organizations believe their customers trust their organizations use of D&A

· 70% of organizations use D&A to monitor business performance spot fraud, drive strategy and change and understand how products are used

· With the exception od D&A regulatory compliance, organizations tend to struggle to achieve excellence across the 4 D&A trust anchors of quality, effectiveness, integrity and resilience.

· 72% of healthcare organizations use D7 A to drive process efficiency and find new customers

· Across the analytics lifecycle 38% of organizations have the most trust in identifying and sourcing data and only 10% have the most trust in measuring the effectiveness of analytics

· 47% organizations believe their data analysts have the right skills to continuously push forward with D&A

 

4 Anchors.

 

1.-Trust in the data and the analytics

2- Effectiveness

3.- Integrity

4- Operational control

 

Discussion No. 2 Comment this post (CC)

The first topic of discussion for this week two is very important since we are in an era where technology and digitalization have created a new form of development in business, taking advantage of all possible information and eliminating what we do not need. The video “Building Trust in Analytics” by Anonymous, (2017), mentions the importance and relationship that exists between trust and data, since they form anchors of effectiveness, integrity and reliance or operational control. (Anonymous, 2017).

The article “Investigating the adoption of big data analytics in healthcare by Shahbaz, M., Gao, C., Zhai, L., Shahzad, F., & Hu, Y. (2019), mentions the importance that the use of big data analytic has had in the area of ​​health care since it has opened new paths to exploit areas that were not previously related to the profit of the organization; In this industry the quality and effectiveness of the information obtained from the data is very important for doctors to make decisions related to the health of a patient.( Shahbaz, M., Gao, C., Zhai, L., Shahzad, F., & Hu, Y., 2019)

I think that just as a fraud to be cataloged as such it must have the 3 elements of the fraud triangle that are: opportunity, rationalization and pressure, also the confidence in the data must have the 4 anchors: quality, effectiveness, integrity and resilience or operational control, each of those elements are necessary; For example, in the case of the health care industry, the data needs to have quality so that the information is effective for the purpose that was selected demonstrating integrity, and with a view to an operational control that monitors the results obtained in order to continue improving the future outcomes. The article “The future of big data in facilities management”, by Ahmed, V., Tezel, A., Aziz, Z., & Sibley, M. (2017), mentions how data analytic can influence in a positive and accurate way business in several sectors such as: better planning, business opportunities, fraud detection, among others, but for all this to happen there is a need to have trust in the data and thus avoid unnecessary risks.( Ahmed, V., Tezel, A., Aziz, Z., & Sibley, M.,2017).