Unit III

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Course Learning Outcomes for Unit III Upon completion of this unit, students should be able to:

2. Examine emerging trends in information technology for organizations. 2.2 Explain emerging technologies in business.

7. Discuss an information technology infrastructure.

7.1 Discuss how business intelligence systems are used for reporting and data analytics. Required Unit Resources Chapter 5: IT Infrastructure and Emerging Technologies Chapter 6: Foundations of Business Intelligence: Databases and Information Management In order to access the following resource, click the link below. Insight. (2015, May 5). Rockwell automation fuels the oil and gas industry with IoT [Video]. YouTube.

https://www.youtube.com/watch?v=T7Fm5thPE4o A transcript of the video is available within the YouTube player by clicking on the three dots below the video title on the right. Closed-captioning can be turned on by clicking the “cc” icon at the bottom of the video. Unit Lesson

What Is Information Technology (IT) Infrastructure? IT infrastructure includes the shared technology resources that provide the platform supporting our information system applications. An IT infrastructure includes seven major components: consultants and system integrators, computer hardware platforms, data management and storage, enterprise software applications, networking and telecommunications technology, Internet platforms, and operating system platforms. As you can see, there is more to a firm’s IT infrastructure than just hardware and software. IT infrastructure includes everything technical that supports the business. It supports both the business and IT strategies. Think of it this way: If our strategy is to offer our customer a specific service such as electronic invoicing (EDI), how can we do that without the infrastructure in place to carry out that goal? The IT infrastructure in this case is the EDI software, the hardware (i.e., a server, database, and the Internet), the personnel, the educational services, the management services, and so on.

Evolution of IT Infrastructure How has IT infrastructure evolved over time? Most of us have a sense of the answer to this question. It is enormous! Just look at computers—the first ones were huge. Businesses used mainframes that were the size of trucks, and now servers are the size of a desktop. Simple applications of the past have now become suites, or bundles of applications that can work together. Now, there are enterprise-level applications that help improve an organization’s productivity and efficiency via a collection of programs with common business applications. They are designed to be customizable to solve enterprise-wide problems rather than personnel or departmental problems.

UNIT III STUDY GUIDE IT Infrastructure, Emerging Technologies, and Foundations of Business Intelligence

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In addition, there are newly emerging enterprise-level tools such as enterprise database management software. Again, enterprise-level tools take the already existing tools to a different level to answer the need for more storage and enterprise-wide sharing. Years ago, dialing into the Internet meant using a slow modem. Now, businesses can use fiber-optic and wireless technologies. In the past, for small- to medium-sized organizations, many of the emerging technologies were out of reach and were mostly cost prohibitive. Now, these businesses can turn to the cloud and service providers to gain access to technologies that were previously out of reach. The video below displays how an industrial manufacturer, Microsoft, and the Internet of Things (IoT) combine to provide innovative improvements to the worldwide oil and gas supply chain. View the video Rockwell Automation Fuels the Oil and Gas Industry with IoT. (A transcript of the video is available within the YouTube player by clicking on the three dots below the video title on the right. Closed- captioning can be turned on by clicking the “cc” icon at the bottom of the video.

Current Trends in Technology We just mentioned one trend, which is cloud computing. Cloud computing offers many on-demand services. One good example is software as a service (SaaS). This service allows the customer to take advantage of highly beneficial applications via a yearly subscription fee rather than paying a large purchase cost. Cloud computing helps businesses reduce their IT overhead costs while making their systems more efficient by offering access to computing capacity that many small- to medium-sized businesses might not be able to afford. Let’s examine the opening case in Chapter 5, “American Airlines Heads for the Cloud.” In this scenario, American Airlines needed to upgrade their IT to improve customer service and remain competitive. However, instead of upgrading its own IT infrastructure and develop the new applications the traditional way (on premise computing center), the company decided it would be more cost-effective to use cloud computing. This decision meant that the company did not need to invest heavily in its own IT infrastructure or in the personnel needed to develop and maintain it. By migrating a portion of their systems to IBM cloud services, the company was able to get up and running in half the time and for less cost had they chosen to upgrade their own IT infrastructure. The new systems significantly improve system performance and reliability and reduce end-user response time. Another benefit to cloud computing is that the cloud service is scalable, which means that as the company grows, the cloud services can grow with it. Although there seems to be advantages for using cloud services, there are also some disadvantages. Even though users can access data via the cloud from just about anywhere, there are security risks for many businesses and concerns about the transfer of IT responsibilities to a third party. For example, how well does the vendor monitor security threats? How fast do they respond to issues? How often does the vender have downtime? There are many things to consider when transferring IT responsibilities to a third party. Virtualization is another recent trend. Many organizations are moving their physical servers to a virtual platform rather than being restricted by the physical restraints of the server box. In a virtual world, you can assign resources dynamically, and all of the servers on a host share the whole. Another recent trend is wearable technology—devices that contain multiple sensors that can track a variety of activities. For example, a fitness tracker can track the number of steps a person walks and their heart rate, and it can track how long they performed the activity. There are a variety of wearable technologies such as fitness trackers, smartwatches, smart jewelry, smart clothing, implantables, and head-mounted displays. Wearable devices in business can help increase employee productivity by providing information instantly without the user having to interrupt whatever task he or she is working on. This type of technology is helping businesses better understand their employees and their customers by learning about what they do every day, what they do to stay healthy, where they go, and how they feel. There are many benefits to wearable

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technology, but there are also concerns about privacy and about how the sensitive data are used by businesses.

Business Intelligence (BI) Suppose you have over 100 small candy stores across the United States. You want to collect data about pricing changes from the vendors and information about marketing trends. Then, you might also want to collect information from external sources like your competitor data or demographic data. How would you store this information? Well, you will store it in a data warehouse. Data warehouses are a part of your BI infrastructure. It is through this infrastructure that you can use tools like analytics and data mining to look for patterns in your data that you cannot see by just looking at query or report results. The first analytical method is online analytical processing (OLAP), which allows the user to view data in different ways by using different dimensions. This is commonly referred to as using a data cube. How could this be used for our example? Well, we could pull information on the best-selling candy bar, the average price, and the day of the week and the month of the year when the most candy bars are sold. Would that get us closer to knowing what kind of discount offers to put in our stores? It would, but this would not provide us with enough information. The next common analytical method is data mining. Data mining is more complex and looks for hidden patterns and relationships. Again, let’s apply this to our previous example. The results of our data mining could show us the best-selling candy bar, the average price, and the day of the week and month of the year when we sell the most candy bars. It may also tell us that the majority of the time that people buy candy bars is when they also buy a soda or coffee. Now, what can our marketing department do with that information? They can bundle products together and advertise them in the store windows and at the gas pumps: “Buy a soda and candy bar, and you can get 50 cents off.” This is a simple example. Just imagine the rows of data that retailers like Amazon.com have stored in databases and data warehouses! Now, there are Web mining tools that help organizations understand customers’ Internet patterns, including which websites they frequent, what they buy, what they do not buy, and how long they spent on the websites. All of this is large data, and it is valuable data. Let’s take a look at the opening case in Chapter 6, “Domino’s Pizza Masters Data One Pizza at a Time.” In this example, we can see that data can be difficult to access and analyze if systems are not configured properly. The company had millions of records with data from nearly 15,000 outlets in 70 countries serving millions of pizzas each year, but they were not able to organize the data to be analyzed because much of the data was in 85,000 different internal and external unintegrated sources (Marr, 2018, as cited in Laudon & Laudon, 2022). By implementing a data warehouse, the company was able to consolidate the data from the various repositories to a single location. Consolidating the data makes it much easier to access and manipulate into usable information. With its new data warehouse, the company now has a single, consistent source of data to use to create one-to-one buying experiences across multiple points of interaction with customers and to drive the growth of individual stores and franchise groups.

Summary Organizations can make big decisions based on their data. They pay a huge amount of money to store and analyze the collected data. As an IT professional, it is your job to protect the data and to help ensure data quality and integrity. There are several concepts—other than the ones previously mentioned—that are also important to this field. The most important involve the need for organizations to set effective information policies and to have adequate data governance across the enterprise. We will cover more on these topics in a future lesson.

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Reference Laudon, K. C., & Laudon, J. L. (2022). Management information systems: Managing the digital firm (17th ed.).

Pearson. Suggested Unit Resources In order to access the following resources, click the links below. To reinforce the concepts from this unit, you are encouraged to review the following:

• Chapter 5 PowerPoint Presentation (PDF for Chapter 5 PowerPoint presentation)

• Chapter 6 PowerPoint Presentation (PDF for Chapter 6 PowerPoint presentation)

The following article introduces design details, key technologies, and practical implementation methods of smart clothing systems. Chen, M., Ma, Y., Song, J., Lai, C.-F., & Hu, B. (2016). Smart clothing: Connecting human with clouds and big

data for sustainable health monitoring. Mobile Networks and Applications, 21(5), 825–845. https://libraryresources.columbiasouthern.edu/login?url=https://search.ebscohost.com/login.aspx?dire ct=true&db=asn&AN=118670600&site=ehost-live&scope=site

The following video cases mentioned in your eTextbook augment the information presented in the assigned chapter readings. You are encouraged to review the Chapter 5 and 6 video cases linked below. A transcript can be accessed for each video within the YouTube player by clicking on the three dots below the video title on the right. Closed-captioning can be turned on by clicking the “cc” icon at the bottom of each video. Amazon Web Services. (2012, July 30). Netflix on AWS - Customer Success Story [Video]. YouTube.

https://www.youtube.com/watch?v=oH3PAGZJewA The Verge. (2015, January 28). ESPN and the future of sports coverage [Video]. YouTube.

https://www.youtube.com/watch?v=zv7q1Wx_QHw