Decisions about Data

Data collection has been around for years in one form or another. The implementation of the No Child Left Behind Act stimulated dedicated educators to learn the correlation between data driven decision-making and successful school improvement plans. The legislative goal was to ensure academic success across all socioeconomic frontiers. Districts across the country were steered into driving their instruction with data and teacher collaboration. This has lead to districts that have successfully found the correlation between data driven decision-making and success.

The choice to have various copies of the information in case of loss and ease of transfer.

Informed decision-making is an important aspect for working in the government. According to Milakovich and Gordon, provide some examples of how information technology can be used to assist bureaucrats in decision-making?

According to Berson and Dubov (2011), there are four typical categories of drivers that explain the need for data management: Business Development, Sales and Marketing; Customer Service; Risk, Privacy, Compliance and Control; and Operational

Discuss the importance of data accuracy. Inaccurate data leads to inaccurate information. What can be some of the consequences of data inaccuracy? What can be done to ensure data accuracy? Data accuracy is important because inaccurate data leads may lead to such things as the closing down of business, it may also lead to the loosing of jobs, and it may also lead to the failure of a new product. To ensure that one’s data is accurate one may double check the data given to them, as well as has more than one person researching the data they are researching.

Data management is vital to any business as this is a key tool to an organisations business improvement, as you can refer back to data, and compare them against benchmarks. Analysing data can provide evidence for possible future structure such as identify trends, as well as indicate where improvements can be made. However there are strict procedures to be followed when collecting and storing data.

* Collect and store data which may be converted into information at some later point in time

The two main methods of storage are manual and electronic, both methods having their own benefits. The data can be used for analysis to assist the organisation fulfil its future goals and overall vision. All data must be stored in such a way that it complies with the regulations put in place by the government. This not only protects the organisation, but each and every member of the public.

One of the biggest lessons I have learned from my time in oncology is that medicine is not practiced in a vacuum. Contrary to popular belief, physicians do not make decisions, especially life changing ones, solely based on the knowledge in their heads. Instead, physicians often take advantage of the wealth of resources that are available to them including health guidelines, treatment protocols, research studies and the opinions of esteemed colleagues. It is the job of the physician to offer the best treatment possible to their patients and this often means leaning on the insights of others to make well-informed decisions. As a medical student, and later in my career as a physician, I will undoubtedly run into situations where I will have to

“Every truth has two sides; it is as well to look at both, before we commit ourselves to either” - Aesop

Evidence-based decision making exemplifies a practice of conscientiously using the best obtainable data and evidence when making managerial decisions. There are five steps in the evidence-based decision model. The first step is to identify the problem or opportunity, step two is to gather internal evidence or information about the problem and evaluate its relevance and validity. The third step is to gather external evidence about the problem from published research, step four is to gather views from stakeholders affected by decision and consider ethical implications. Finally, the fifth step is to integrate and critically appraise all data and then make a decision (Kreitner & Kinicki, 2013).

2. Which of the following is intended to solve the problem that financial data used in one application is not easily transferable to other applications?

b) One the decision that had little impact or no effect on anyone at all was when I bought an ice cream the last Saturday. This decision didn’t have any impact because I was thinking in only by myself and nobody was involved with this and the consequences only affect myself.

3. What would you recommend as effective methods for this organisation to store the data, and why? (Give two different options)

The importance of the relevance of the data has been identified since the very early work in context-aware ubiquitous systems. Despite of its importance few works have been carried out to quantify the QoC and ensure the quality of the information on which the decisions and actions of contextaware systems are based. Moreover, many decision support techniques are insufficient to address the runtime uncertainty in the context information as they do not assess the QoC in an end-to-end fashion. We formulate the related work into two parts: 1) QoC attributes and modeling aspects 2) Runtime decision support addressing uncertainty A. QoC attributes and modeling aspects QoC attributes and their modeling comes into play to capture the uncertainties in context data. A well designed model is a key assessor to the quality of the context.