REFLECTION PAPER ABOUT BUSINESS INTELLIGENCE

this paper is a part of my portfolio. the course is CIM 605 Business Intelligence , please write a paper reflection about what I did in class such as weekly group work and discussion to reach thes goals:1- Apply appropriate research methods to problems in information and communication and evaluate solutions to problems.2-Articulate the interrelatedness of rhetoric and information sciences, especially decision-making, human behavior in institutional settings, and the impact of advances in technology in communications.

Forum 3: Making today’s business decisions.
1313
Making high-stakes business decisions has always been hard. Eric Bonabeau asserts that in recent decades, it has become tougher than ever. How does he support his assertion? Do you think the author provided sufficient evidence to support his assertion? Do you agree with his view point? Why or why not?

Remember this is a discussion forum and we will use this during class. You must participate and contribute to the discussion during class in a significant way by entering into a dialogue with several of your classmates in order to receive full credit.
———-
Forum 4: Intuition – Can You Trust Your Gut?
99
The choices facing managers and the data requiring analysis have multiplied even as the time for analyzing them has shrunk. One simple decision-making tool, human intuition, seems to offer a reliable alternative to painstaking fact gathering and analysis.

Eric Bonabeau references the book, Intuition at Work, by decision-making consultant, Gary Klein’s book. In the book Klein expresses the common wisdom that intuition is “at the center of the decision-making process” and that analysis is, at best, a supporting tool for making intuitive decisions. Encouraged by scientific research on intuition, many top managers when faced with complex decisions feel increasingly confident that they can just trust their gut. Bonabeau disagrees:

“The trust in intuition is understandable. But it’s also dangerous. Intuition has its place in decision
making–you should not ignore your instincts any more than you should ignore your conscience–
but anyone who thinks that intuition is a substitute for reason is indulging in a romantic delusion”.

So make a choice. Which view point do you favor? Present an argument supporting your view.
———
M1Q1 – The Second Road of Thought
11
Golsby-Smith states that Aristotle created two roads (paths) of thought: analytics and rhetoric. Each path was meant to address a different problem domain because the problem being addressed was different.

What type of problem does the analytic path produce? What type of solution does the rhetoric path produce? Golsby-Smith claims that western thought invested more heavily in the analytic path (i.e., the scientific approach). Why does he think that is a mistake? Do you agree or not?
——
M1Q2 – Competing on Analytics
11
Davenport is making an argument in favor of using analytics to support decision-making.Do you agree with his overall premise? Why or why not? What were some of his most persuasive arguments?
—–
M1Q3 – Harrah’s Casino
Why is Loveman’s marketing approach so different from the traditional marketing done by other casinos? What kind of proof of success did he offer?

How does Harrah’s reward their employees? Do you think this method is good for the casino? Is it good for the employees?

Hint: Pay special attention to his use of data.

——–
Drop box for your Module 1 Summary Report

Abstract
Data Analytics is defined as the science of examining data with the goal of discovering, modeling, and transforming useful information. Skilled professionals need to utilize from this process of data analyzing in order for them to make better decisions and thus make a better business.
Methods: First, company should develop a plan which is to determine what data is collected. Data analytics and presentation must find an adequate explanation for the development of solutions. It is must that verify the authenticity of the data recording and contradictions. it is supposed to choose the data collection method and adjusted based on user feedback to get to a convincing and successful analysis.
Results : Having the ability to use IT services along with focusing on business goals will not only provide us with the advantage of creating better communication with IT management, but also will provide the foundation for planning future services. In the article “The Importance of big Data Analytics in Business,” Wagner states that “The majority of CIOs believe the IT department can increase the value it delivers to the organization by improving cost measurement.”
Conclusion: data analytics reduces costs. Data analytics on an ongoing basis is good to help the survival of the company and access to meet the needs of customers. Data analytics helps to make the right decision quickly and to avoid risks of falling. Data analytics show us how to introduce new products or new services and stay in the progress on your competitors.

Data Analytics is defined as the science of examining data with the goal of discovering, modeling, and transforming useful information. Skilled professionals need to utilize from this process of data analyzing in order for them to make better decisions and thus make a better business.
Data analytics is useful in identifying trends and weaknesses. Data analytics also allow us to determine any conditions that can be utilized in making future decisions. Moreover, data analytics can draw out the relevant information so that it can be analyzed, then transformed and used in future decisions. However, we cannot use this process on large amount of data since traditional storage environment and processing times cannot be maintained.
In order to be successful in the work field, the majority of data is collected by IT, which shares data that is useful for the business. IT services is important to prove the value of IT to business. Having the ability to measure the business outcomes by using IT services is more important than measuring the costs. Having the ability to use IT services along with focusing on business goals will not only provide us with the advantage of creating better communication with IT management, but also will provide the foundation for planning future services. In the article “The Importance of big Data Analytics in Business,” Wagner states that “The majority of CIOs believe the IT department can increase the value it delivers to the organization by improving cost measurement.” (Dave Wagner, 2014)
Managing the big data that is trooping in many organizations every day has become a challenge to many companies. Even if the big data offers a chance for the tremendous growth, good data analytics is crucial in maximizing sales. For many years, McDonalds has stood as an American capitalism great success stories. However, the company has faced low sales in the last few years. McDonald’s has been experiencing low sales, and the company has been trying to go back to the track. According to the study by Ton (2014), the company’s problems started sprouting because of the operational mishaps, competition from various companies, for example, Burger King, Shake Shack among others. McDonald’s has been using the data analytics for some time now. For the years they’ve used the model, the company has not increased the sales. On the other hand, Wendy’s has been using the data analytics a tool that has worked for them even though they are also registering low sales.
In June 2015, the company was devastated because of the low sales and they decided to stop reporting their low financial numbers. However, Burger Chain continued reporting their sales and focusing on the long-term progress. Wendy’s are continuing to give their reports on the sales growth since their sales are highly rising. According to the report by Hill et al. (2016), the strategy McDonalds is using to keep their investors in the dark is not working and will not change the McDonald’s fortunes. McDonald’s data analytics failed because they were unable to meet the need for the speed, address the data quality, understand the data and work on the data to display meaningful results (Runkler, 2012).
McDonald’s introduced the data analytics tool to improve their customer care and the sales that had been dropping. The company implemented the software in all their operational areas, and they thought it will solve the statistically oriented issues. Unlike the McDonald’s, Wendy’s has been using the data analytics that has worked, but their sales have continued to fall. The data analytic software is helping them in analyzing the daily sales and labor costs. Some of the few elements that have made the company to succeed in their data analytics are that they replaced their MyMicros with their WebFOCUS. One of the biggest mistakes that the company has been making regarding the data analytics is the customer service. The annual customer service satisfaction shows that the company does not use the data analytics to upgrade on their customer care services (Runkler, 2012).
The data analytics has been working because it is often updated. According to Hills & Jones (2016), Wendy’s data analytics are refreshed six times daily that assist the managers to keep safely the metrics. Wendy’s data analytics did not work overnight but took a lot of time to practice and update.
Companies should use the data analytics for various reasons. According to the study that was conducted by Minelli, Chambers & Dhiraj (2013), the data analytics reduces the costs. The data analytics assist the companies to keep large amounts of data that assist them in reaching their customers and manage their sales. Secondly, the data analytics should be used to make fast decisions. Big companies review their data when making decisions that affect their company. A company that has highly succeeded in the use of the data analytics is Caesars in making faster decisions. Data analytics can also be used when introducing new products and services and staying ahead of the competitors.
To improve the quality and funding requirements, the company must develop a clear plan to data collection and analysis. First, it should develop a plan which is to determine what data is collected. It is important to confirm the quality of the data collected. The development of data is about known how the data will be collected.
Data analytics and presentation must find an adequate explanation for the development of solutions. It must that find an adequate explanation for the development of solutions by data analytics and presentation. To reach a suitable solution must verify the validity of the data. It is must that verify the authenticity of the data recording and contradictions. it is supposed to choose the data collection method and adjusted based on user feedback to get to a convincing and successful analysis.
If employees capacity can make good decision, the company do not have to conduct data analytics. There are employees understand the needs of customers. They have sufficient information to make appropriate decisions quickly. On addition, they know the customer tastes.
Companies with a culture of evidence-based decision making see to it that business rules are continually assessed and improved by articulating them clearly and ensuring consistency across the company ( Jeanne, 2013). There is evidence explicit and clear need to evaluate and improve only. On the other hand, do not need to do data analytics. Sometimes there are clear expectations for modification and development. In addition, there is a clear plan to improve the performance of each individual.
Data analytic is important to fix any problem in company. In addition, decision-makers have to focus on specific data which is relevant to make a good decision. It is important to search about right information which allowed seeing the problem, and tells there is a problem or there are chances to improve or to be unique. Also, updating information as fast as possible is assist to get data which gives a good indication to take a successful decision.
When making the decision, it must consider the implications of this decision from all respects. While decision-maker collected data to make a perfect decision, they have to make sure that decision make the company in advance for the future, not only so far because it is important to avoid future obstacles.
When considering the number of times a repeat purchase, it means a lot. From this point it can be troubleshooting and the reason for the lack of sales. If the sales go down in some product that means it is not good and maker-decision have to know there are problems. On the other hand, they try to found it. It needs to be amended or add something to be unique. By this data must discover what is problem and try to solve it.
Finally, all company should use data analytics because it is a better way to found problem and fix it faster. Company should update the data analytics on a daily basis to get to the best and fastest results. This is one of the most important things you must found within your company to not only understand your business, but to drive your business forward and keep it unique.
———————————–
M2Q1 – Data Warehouses and Data Mining
Jerzy Surma’s description of a data warehouse is a fairly technical paper. It is geared toward technical practitioners. Notice the difference in tone between his paper and mine (see my description of a data warehouse). Which do you think is mor

this paper is a part of my portfolio. the course is CIM 605 Business Intelligence , please write a paper reflection about what I did in class such as weekly group work and discussion to reach thes goals:1- Apply appropriate research methods to problems in information and communication and evaluate solutions to problems.2-Articulate the interrelatedness of rhetoric and information sciences, especially decision-making, human behavior in institutional settings, and the impact of advances in technology in communications.

Forum 3: Making today’s business decisions.
1313
Making high-stakes business decisions has always been hard. Eric Bonabeau asserts that in recent decades, it has become tougher than ever. How does he support his assertion? Do you think the author provided sufficient evidence to support his assertion? Do you agree with his view point? Why or why not?

Remember this is a discussion forum and we will use this during class. You must participate and contribute to the discussion during class in a significant way by entering into a dialogue with several of your classmates in order to receive full credit.
———-
Forum 4: Intuition – Can You Trust Your Gut?
99
The choices facing managers and the data requiring analysis have multiplied even as the time for analyzing them has shrunk. One simple decision-making tool, human intuition, seems to offer a reliable alternative to painstaking fact gathering and analysis.

Eric Bonabeau references the book, Intuition at Work, by decision-making consultant, Gary Klein’s book. In the book Klein expresses the common wisdom that intuition is “at the center of the decision-making process” and that analysis is, at best, a supporting tool for making intuitive decisions. Encouraged by scientific research on intuition, many top managers when faced with complex decisions feel increasingly confident that they can just trust their gut. Bonabeau disagrees:

“The trust in intuition is understandable. But it’s also dangerous. Intuition has its place in decision
making–you should not ignore your instincts any more than you should ignore your conscience–
but anyone who thinks that intuition is a substitute for reason is indulging in a romantic delusion”.

So make a choice. Which view point do you favor? Present an argument supporting your view.
———
M1Q1 – The Second Road of Thought
11
Golsby-Smith states that Aristotle created two roads (paths) of thought: analytics and rhetoric. Each path was meant to address a different problem domain because the problem being addressed was different.

What type of problem does the analytic path produce? What type of solution does the rhetoric path produce? Golsby-Smith claims that western thought invested more heavily in the analytic path (i.e., the scientific approach). Why does he think that is a mistake? Do you agree or not?
——
M1Q2 – Competing on Analytics
11
Davenport is making an argument in favor of using analytics to support decision-making.Do you agree with his overall premise? Why or why not? What were some of his most persuasive arguments?
—–
M1Q3 – Harrah’s Casino
Why is Loveman’s marketing approach so different from the traditional marketing done by other casinos? What kind of proof of success did he offer?

How does Harrah’s reward their employees? Do you think this method is good for the casino? Is it good for the employees?

Hint: Pay special attention to his use of data.

——–
Drop box for your Module 1 Summary Report

Abstract
Data Analytics is defined as the science of examining data with the goal of discovering, modeling, and transforming useful information. Skilled professionals need to utilize from this process of data analyzing in order for them to make better decisions and thus make a better business.
Methods: First, company should develop a plan which is to determine what data is collected. Data analytics and presentation must find an adequate explanation for the development of solutions. It is must that verify the authenticity of the data recording and contradictions. it is supposed to choose the data collection method and adjusted based on user feedback to get to a convincing and successful analysis.
Results : Having the ability to use IT services along with focusing on business goals will not only provide us with the advantage of creating better communication with IT management, but also will provide the foundation for planning future services. In the article “The Importance of big Data Analytics in Business,” Wagner states that “The majority of CIOs believe the IT department can increase the value it delivers to the organization by improving cost measurement.”
Conclusion: data analytics reduces costs. Data analytics on an ongoing basis is good to help the survival of the company and access to meet the needs of customers. Data analytics helps to make the right decision quickly and to avoid risks of falling. Data analytics show us how to introduce new products or new services and stay in the progress on your competitors.

Data Analytics is defined as the science of examining data with the goal of discovering, modeling, and transforming useful information. Skilled professionals need to utilize from this process of data analyzing in order for them to make better decisions and thus make a better business.
Data analytics is useful in identifying trends and weaknesses. Data analytics also allow us to determine any conditions that can be utilized in making future decisions. Moreover, data analytics can draw out the relevant information so that it can be analyzed, then transformed and used in future decisions. However, we cannot use this process on large amount of data since traditional storage environment and processing times cannot be maintained.
In order to be successful in the work field, the majority of data is collected by IT, which shares data that is useful for the business. IT services is important to prove the value of IT to business. Having the ability to measure the business outcomes by using IT services is more important than measuring the costs. Having the ability to use IT services along with focusing on business goals will not only provide us with the advantage of creating better communication with IT management, but also will provide the foundation for planning future services. In the article “The Importance of big Data Analytics in Business,” Wagner states that “The majority of CIOs believe the IT department can increase the value it delivers to the organization by improving cost measurement.” (Dave Wagner, 2014)
Managing the big data that is trooping in many organizations every day has become a challenge to many companies. Even if the big data offers a chance for the tremendous growth, good data analytics is crucial in maximizing sales. For many years, McDonalds has stood as an American capitalism great success stories. However, the company has faced low sales in the last few years. McDonald’s has been experiencing low sales, and the company has been trying to go back to the track. According to the study by Ton (2014), the company’s problems started sprouting because of the operational mishaps, competition from various companies, for example, Burger King, Shake Shack among others. McDonald’s has been using the data analytics for some time now. For the years they’ve used the model, the company has not increased the sales. On the other hand, Wendy’s has been using the data analytics a tool that has worked for them even though they are also registering low sales.
In June 2015, the company was devastated because of the low sales and they decided to stop reporting their low financial numbers. However, Burger Chain continued reporting their sales and focusing on the long-term progress. Wendy’s are continuing to give their reports on the sales growth since their sales are highly rising. According to the report by Hill et al. (2016), the strategy McDonalds is using to keep their investors in the dark is not working and will not change the McDonald’s fortunes. McDonald’s data analytics failed because they were unable to meet the need for the speed, address the data quality, understand the data and work on the data to display meaningful results (Runkler, 2012).
McDonald’s introduced the data analytics tool to improve their customer care and the sales that had been dropping. The company implemented the software in all their operational areas, and they thought it will solve the statistically oriented issues. Unlike the McDonald’s, Wendy’s has been using the data analytics that has worked, but their sales have continued to fall. The data analytic software is helping them in analyzing the daily sales and labor costs. Some of the few elements that have made the company to succeed in their data analytics are that they replaced their MyMicros with their WebFOCUS. One of the biggest mistakes that the company has been making regarding the data analytics is the customer service. The annual customer service satisfaction shows that the company does not use the data analytics to upgrade on their customer care services (Runkler, 2012).
The data analytics has been working because it is often updated. According to Hills & Jones (2016), Wendy’s data analytics are refreshed six times daily that assist the managers to keep safely the metrics. Wendy’s data analytics did not work overnight but took a lot of time to practice and update.
Companies should use the data analytics for various reasons. According to the study that was conducted by Minelli, Chambers & Dhiraj (2013), the data analytics reduces the costs. The data analytics assist the companies to keep large amounts of data that assist them in reaching their customers and manage their sales. Secondly, the data analytics should be used to make fast decisions. Big companies review their data when making decisions that affect their company. A company that has highly succeeded in the use of the data analytics is Caesars in making faster decisions. Data analytics can also be used when introducing new products and services and staying ahead of the competitors.
To improve the quality and funding requirements, the company must develop a clear plan to data collection and analysis. First, it should develop a plan which is to determine what data is collected. It is important to confirm the quality of the data collected. The development of data is about known how the data will be collected.
Data analytics and presentation must find an adequate explanation for the development of solutions. It must that find an adequate explanation for the development of solutions by data analytics and presentation. To reach a suitable solution must verify the validity of the data. It is must that verify the authenticity of the data recording and contradictions. it is supposed to choose the data collection method and adjusted based on user feedback to get to a convincing and successful analysis.
If employees capacity can make good decision, the company do not have to conduct data analytics. There are employees understand the needs of customers. They have sufficient information to make appropriate decisions quickly. On addition, they know the customer tastes.
Companies with a culture of evidence-based decision making see to it that business rules are continually assessed and improved by articulating them clearly and ensuring consistency across the company ( Jeanne, 2013). There is evidence explicit and clear need to evaluate and improve only. On the other hand, do not need to do data analytics. Sometimes there are clear expectations for modification and development. In addition, there is a clear plan to improve the performance of each individual.
Data analytic is important to fix any problem in company. In addition, decision-makers have to focus on specific data which is relevant to make a good decision. It is important to search about right information which allowed seeing the problem, and tells there is a problem or there are chances to improve or to be unique. Also, updating information as fast as possible is assist to get data which gives a good indication to take a successful decision.
When making the decision, it must consider the implications of this decision from all respects. While decision-maker collected data to make a perfect decision, they have to make sure that decision make the company in advance for the future, not only so far because it is important to avoid future obstacles.
When considering the number of times a repeat purchase, it means a lot. From this point it can be troubleshooting and the reason for the lack of sales. If the sales go down in some product that means it is not good and maker-decision have to know there are problems. On the other hand, they try to found it. It needs to be amended or add something to be unique. By this data must discover what is problem and try to solve it.
Finally, all company should use data analytics because it is a better way to found problem and fix it faster. Company should update the data analytics on a daily basis to get to the best and fastest results. This is one of the most important things you must found within your company to not only understand your business, but to drive your business forward and keep it unique.
———————————–
M2Q1 – Data Warehouses and Data Mining
Jerzy Surma’s description of a data warehouse is a fairly technical paper. It is geared toward technical practitioners. Notice the difference in tone between his paper and mine (see my description of a data warehouse). Which do you think is more appropriate for a CIM student?

e appropriate for a CIM student?

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