Speaker 1: Hello everyone and welcome back to BAN 7101 Business Analytics. In this module we're going to discuss reporting and data visualization. This module's learning objectives are as follows. So after this module you should be able to define business reporting and describe its historical evolution, identify the most appropriate type of data visualization, so for example a line graph or a table for a given data set, create an appropriate data visualization in Microsoft Excel for a given data set, and describe the capabilities and limitations of dashboards. The information related to Microsoft Excel is going to be provided in a separate video. I'll provide a link to that video in the description. So what is business reporting and what is its purpose? We've already discussed the vast amount of data that is created by organizations in their day-to-day operations and in their analytics. A report is a simple way to present or summarize that information in order for someone to read it and to make a decision. A report can be formally defined as any communication artifact prepared to convey specific information. So this could be a summary, this could be a select few pieces of information, but the point is that that data or information was carefully selected in order to convey something very specific to its viewer. A report can fulfill many functions. There are reports generated to ensure proper departmental functioning that can let us know if errors are taking place. Reports can be used to simply provide information, to provide the results of an analysis, to persuade others to act, or to create an organizational memory. It may be that different processes or improvements need to be documented and reported so that when new employees come in in the future they're able to take a look at those documents and understand the organizational history. So what is a business report? It's a written document that contains information regarding business matters. The main purpose of report is to improve managerial decisions. So a manager or someone who has decision-making capabilities is given this document in order to make a decision based on the data in it. Source data for these reports can come from inside and outside the organization by the use of extract, transform, load, which we'll talk about in a later module. Reports can be formatted in various ways. Many times they'll just include text or tables. They can also contain graphs or charts. They can be distributed in print, via email, or via a portal or intranet within the organization. That's going to depend upon who actually needs access and who can have access to that report. The general process proceeds in the following way. So data is acquired related to the organization or data that's related to the outside of the organization. Information is generated from that data that leads to decision-making and then the management of processes within the organization. Business reporting provides a cyclical decision-making process based on business functions taking place, which leads to the collection of transactional data. For example, we can find out in a manufacturing organization how many times and when different machine failures took place. That data is then stored. It can then be summarized and reported in different kinds of reports that are then interpreted by a decision-maker who takes action based on the data given to them and that then in turn influences the business functions that originally created that data in the hopes of process improvement. There are several types of business reports. These include metric management reports, which help manage business performance through metrics. These can be service level agreements for externals and key performance indicators or KPIs for internals. These types of reports can be used as part of a Six Sigma process or a total quality management process. These are quite typical in manufacturing. There are also dashboard type reports that are graphical presentations of several performance indicators in a single page using dials or gauges. These give a general summary to the decision-maker about what is happening, what's going well, and what's not going well within the organization based on specific key performance indicators. There are also balanced scorecard type reports. These include financial, customer, business process, and learning and growth indicators. So what is data visualization and what is the primary purpose of data visualization? It's very likely that you have already created and interpreted data visualizations, but you may not have gone terribly deep into the process and purpose of visualization. So your textbook defines data visualization as the use of visual representations to explore, make sense of, and communicate data. And I'm going to put an emphasis here on the communication of data for the purpose of making a decision. We use data visualizations primarily to communicate and to help people make decisions based on what we're communicating about the data. We can talk about the difference between data and information visualization. So data visualization referring to a much lower level of data visualization. Perhaps we're looking at a visualization of specific transactional records. Information visualization, you're going to be looking generally at aggregates, summaries of data, and contextualization of data. I'll remind you that simple text and tables are included under the umbrella of data and information visualization, but the discipline also includes information graphics, scientific visualizations, and statistical graphs. If you do take a look at that tutorial on Microsoft Excel and visualization, you'll see all the different types of charts, graphs, and illustrations that you can create based on different levels of aggregation of data. Let's talk about the history of data visualization. So data visualization is not new. It dates back to the second century AD. Most developments within the discipline have occurred within the last two and a half centuries, and until recently it was not recognized as a formal discipline. So I'm happy to say that now we're taking a look at both the scientific and the artistic sides of data visualization and formalizing them so that we can craft better visualizations and learn how to better communicate using these types of graphics. Today's most popular visual forms date back a few centuries, so this includes John Snow's visualization of the cholera epidemic in the 19th century. It also includes the first pie chart that was created by William Playfair in 1801. Now we'll caution you against the use of the pie chart. Pie charts are quite common, but remember that you can only include one factor, and take a look at how that factor is divided up within that pie chart. So for example, taking a look at the percentages of students enrolled in specific programs at GSU. This is a fairly complicated visualization, so we're taking a look at exports and imports to and from Denmark and Norway from 1700 to 1780. There's quite a bit going on here. We have different axes that are indicating different things. We have a timeline that contrasts the imports line and the exports line, and some shading that indicates the balance in favor of England and the balance against. Similarly, we have this very popular visual of the decimation of Napoleon's army during the 1812 Russian campaign. We have a legend indicating space. This visual is in French, and I don't speak any French, so I can't help you there, but essentially we're looking at the different locations where the army was decimated throughout the campaign. This is arguably one of the most popular multi-dimensional charts. One of the most popular types of visualizations in organizations are that of the performance dashboard. So performance dashboards you may have likely seen already. They're commonly used in business process management software suites, NBI platforms, Google Analytics, YouTube Analytics have these types of dashboards as well. Dashboards provide visual displays of important information that is consolidated and arranged on a single screen so that it can be digested at a single glance and easily drilled in and further explored. So for example, you may see a KPI indicated in either red or green, where green indicates that it is operating at an acceptable level and red indicates that it is not. Here's an example of an executive performance dashboard. You can see on the left you have a summary of margin expenses and revenue indicated with timelines. On the right you have a map as well as different indicators of expenses when they were in nominal or excessive range. The main challenge of designing a dashboard is that you need to display all the required information on a single screen clearly and without distraction in a manner that can be assimilated quickly. This is challenging because you are trying to present so many things at the same time and have them be easily digested by the viewer in a short amount of time. Dashboards typically take a three-layer of information approach, including that of monitoring, analysis, and management. You can see examples of each of these in the visuals here. So monitoring different expenses, analyzing the sales distribution, and perhaps managing sales as well. Some things to look for when using or designing a dashboard. They should use visual components to highlight data and exceptions that require action in a very simple to digest way. Should be transparent to the user, meaning that they require minimal training and are extremely easy to use. You'll notice that a lot of dashboards use similar types of visuals that we might see on a car that most of us are used to interpreting. They'll combine data from a variety of systems into a single summarized and unified view of the business. Enable drill down or drill through to underlying data sources or reports by clicking on them. Present a dynamic real-world view with timely data, so it needs to be updated in real time, and require little coding to implement, deploy, and maintain. This has been a very brief overview of data visualization, reports, and dashboards. In order to get into the nitty-gritty of designing specific visualizations, I highly encourage you to check out the video related to creating visuals in Microsoft Excel. If you have any questions about this, please let me know.