Steps to this project! This project was developed for learners entering a variety of disciplines. It will enable a deeper understanding of how data informs solutions to practical problems with potential impact on your organization or industry. Over this two-week period, you will use mathematical operations and data analysis to solve problems and inform decision making. Using a method similar to the qualitative research process, you will identify an issue and use mathematical formulas or an analytic tool to derive a solution. You will construct graphs, charts, and tables as necessary to inform analysis and interpretation. You will evaluate the results, draw and validate analyses, and communicate key mathematical information. Before you begin, review the Scenario below. Scenario Your supervisor has been assigned to be the interim manager of the IT Help Desk and needs your help. The previous help desk manager retired after many years in that position and never conducted any analysis of his team's performance. Coming into this new job, your supervisor would like to gain more insight into the strengths and challenges of her help desk team. First, you will need to collect data on the help desk tickets. This data will provide insight into the help desk's performance and give you clues on how to improve the unit. You learn that the help desk has several goals. These goals relate to the measurement of key performance metrics, such as the number of days tickets are open and client satisfaction ratings. You would like to know how well the team members achieved these goals under the previous manager. Analysis of the help desk data will help you understand the team’s performance on these goals. You plan to analyze the data using standard statistical methods in Microsoft Excel. However, one of your colleagues suggests that you also use a data analytics tool called Cognos Analytics, which could help you uncover hidden information. Cognos Analytics can also create graphic depictions of the key information to help you visualize the data. You decide to use both approaches. Your task is to conduct data analysis and prepare a final report for your supervisor about your findings. Your report will also include a set of recommended solutions for improving the performance of the help desk. Once you have reviewed the scenario, review the project overview, approximate time commitment, and competencies that you will be responsible for in this project. Nine steps will lead you through this project. Each step should take no more than two hours to complete. Continue with Step 1: Refresh Your Math, Statistics, and Excel Skills. Step 1: Refresh Your Math, Statistics, and Excel Skills Everyone has a different background. As in previous projects, you will start by assessing your current baseline. First, think about what it means to engage in quantitative processes. Next, refresh your skills in math, statistics, and Excel. You will evaluate how much you already know and where you need to concentrate more attention. If you need help outside the classroom, you can access tutoring by selecting Tutoring Assistance under Resources in your classroom. There are also videos when you access tutoring help and other resources to help you complete this project successfully. Once you have a good idea of your skill levels in math and stats, and you know where to go for help, move on to Step 2, where you will apply some of your stats knowledge. Remember to choose the instructions of the course in which you are currently enrolled. Step 2: Opening and Saving an Excel Spreadsheet In this step, you will be opening and saving an Excel spreadsheet. Download the Technology Template. Note: There are four worksheets or tabs in this Excel spreadsheet. Take a few minutes to review the spreadsheet in its entirety. The four worksheet titles and the purpose of each worksheet are as follows. • • • • IT Help Desk Data—contains the data to be analyzed Data Legend—provides information about the data. Statistical Analysis—used in conjunction with Excel functions to determine the average number of days the tickets are open, the distribution of the requester's seniority, the type and severity of the problem, the assigned priority level, and the end user satisfaction level. The missing information may then be filled in as it is calculated. QR Analysis Essay—provides essay questions to answer after you perform your analysis using Excel and Cognos. Answers should be entered directly inside each box. Next, open the Excel file and go to Save As to rename it. Use the name format YourLastName Project 4. This file contains the data that you will manipulate and analyze. You will add tabs in the next steps to build an Excel workbook for this project. Step 3: Use Functions to Summarize the Data In this step, you'll begin to see patterns in the data that inform the “story” of the data table that you have prepared up to this point. Note: You should strive to work through the first four steps this week. Take a breather here if you need it. Check in with your instructor as needed. In the Excel spreadsheet Technology Template that you have downloaded, review the Statistical Analysis worksheet. You will use the COUNTIF and SUM Function in Excel to prepare the data for future analysis. This will include some simple statistical analysis as well as charts and graphs to present the data. Use Excel formulas to fill in the gray cells under the column labeled “Count” in the five tables in that worksheet. A. Summarize the IT data by presenting categories of data in summary tables and counting them, totaling them, and calculating percentages: o Use the COUNTIF Function to count each item in each table. o Use the SUM Function to total the tables when required. o Calculate percentages for each table as required. Note: Format cells appropriately. Remember to make smart use of reference cells in formulas (avoid typing in numbers or text into formulas—instead, point to other cells) and use relative and absolute cell references to make copying formulas faster and easier. Your supervisor will look for your appropriate use of these tools! B. Complete your analysis based on the results that appear. Answer the following questions by typing into the text box in the "QR Analysis Essay" tab: • • • • Which types of employees are most likely and least likely to open a ticket? Which types of problems are most and least common? What can you tell about the satisfaction level? What can you tell about the number of days a ticket is open? Take Note Don’t forget to format cells appropriately. Make smart use of reference cells in formulas (avoid typing in numbers or text into formulas—instead, point to other cells), and use relative and absolute cell references to make copying formulas faster and easier. Your supervisor will look for your appropriate use of these tools! Step 4: Add Information to Your Spreadsheet In this step, things get interesting! You will expand your analysis by employing descriptive statistics, or summary statistics, using Excel formulas. Now you will calculate mean, median, and mode for the categories of data and derive the deviation, variance, dispersion, and distribution. Format all the results to two decimal places. In Section 2 of the Statistical Analysis tab of the Excel spreadsheet Technology Template, use the appropriate Excel function to complete the table. Calculate the summary statistics of the DaysOpen data on the IT-Help-Desk-Data tab (Column 1). Use the summary statistic Excel functions of =AVERAGE, =MEDIAN, =MODE, =STDEV.S, =VAR.S, =KURT, =SKEW, =MIN, =MAX, =SUM, and =COUNT to derive these statistics for the three data categories. Standard error and range should also be calculated. Step 5: Use the Data Analysis Toolpak Now that you have calculated descriptive statistics using individual Excel functions, we'll look at another approach. Did you know that you can generate the same descriptive statistics in one easy step? Now, you will use Excel's built-in Analysis Toolpak, an add-in that allows you to work with statistics and confirm the answers of your summary statistics. It will help you to save time by performing various complex analyses based on your needs. You will first need to make sure the toolpak is enabled. Feel free to references How to Enable Data Analysis Toolpak for assistance. When you have completed that process successfully, you will see the words "Data Analysis" or an icon on the top right corner on the Data tab. Select Data Analysis and then choose Descriptive Analysis from the list. Note: There may be some minor differences in the answers depending on the version of Excel you are using. Mac users will need Excel 2016 or later to download the toolpak. When you have succesfully enabled the Data Analysis Toolpak, proceed to the tasks below to calculate the statistics using the toolpak. A. The next task will be to provide the input and output. Since you want to have statistics for the DaysOpen data, you will provide the location of the data on the spreadsheet in the input box. Indicate the inclusive cells for the selected categories. To do so, type in the field or capture the column with your mouse, and the field will show in the input range. Check the labels box so you have titles for the categories. Then select New Worksheet Ply, and your output will be a new sheet on your tab. B. Label your new sheet "Summary Stats" and format the columns for readability. C. Compare your calculations from the data analysis feature to the ones you got in the previous step, using individual functions. You should not have a large disparity. This tool is handy for quick computations, and you will use it again to create your pivot table in the next step. Step 6: Create Visual Representations of the Data: Charts and Graphs Where would we be without the ability to view data in charts? It is sometimes easier to grasp the context of data if we can see it captured in an image. Graphs and charts help readers digest and interpret information more quickly, consistent with the familiar adage "a picture is worth a thousand words." Working with Excel Charts will provide an overview of the type of charts available such as pie and bar charts. Refer to it to create a histogram along with Use the Analysis Toolpak as needed. In this step, you will add a new tab, name it "Graphs," and provide the following graphs in the worksheet: A. pie charts showing o the distributions of requestors' seniority and o types of problem B. bar charts showing o the distributions of the severity of the problems and o priority level assigned Be sure to select data labels and create legends for each graph. Step 7: Copy and Sort Data You've accomplished a lot with your data set, summary stats, and histograms. In this step, you will copy and sort data in an Excel worksheet and create a tab for sorted data. You will be able to use this rearrangement of data when you are conducting quantitative analysis. This skill is useful for reporting purposes and can be applied to any Excel application. This step will introduce you to a powerful, state-of-the-art data analytics tool, IBM's Cognos Analytics. This dynamic tool supports quantitative reasoning. Click the following resources to learn about Cognos Analytics and to complete this part of the project: • Review Cognos Analytics to learn more about how it can be effectively applied to data. • Use Getting Started With Cognos Analytics to create a free trial account with Cognos Analytics, log in to it, import your IT help desk data into Cognos Analytics, and review the Cognos Analytics tutorials. Finally, you will analyze the IT help desk data using Cognos Analytics. Use the knowledge and techniques that you learned to analyze the data set with Cognos Analytics. Then answer the following questions and type your answers into the QR Analysis Essay tab. • • • • How is the help desk department performing? Which specific ITOwner (help desk technician) is a high performer? Which ITOwner is the lowest performer? What relevant information about the help desk did you uncover from your analysis? What recommendations do you have for the help desk? • Step 8: Submit Your Completed Workbook with Responses and Analysis You've done a lot of work and should now be prepared to manipulate data fields, analyze data, and create reports that your boss may request in the future. You've learned how to create a multi-tabbed workbook in Excel and explored many ways data can be manipulated and presented to support your summaries and findings. Now that you have completed your analysis, it is time to share what you have found. Answer the questions listed below and in the QR Analysis Essay worksheet in the Technology Template Excel file that you have already downloaded. Your answer to each of the questions should be two to three paragraphs and should provide supporting information, including visualizations, gathered from your analysis using Cognos Analytics. It might be easiest to compose it in a Microsoft Word document and then copy and paste what you've written into your workbook on the QR Analysis Essay tab. You can enlarge the text box to contain your essay and images. Reflect on what you learned from analyzing the data using IBM Cognos Analytics. Incorporate at least two visualizations into your report. Use appropriate mathematical and statistical vocabulary. Keep in mind that you are preparing this report for the head of the department. Provide relevant information that will lead to recommendations that address concerns about the help desk. You should answer the following questions: • • • • How is the help desk department performing? Which specific ITOwner (help desk technician) is a high performer? Which ITOwner is the lowest performer? What relevant information about the help desk did you uncover from your analysis? What recommendations do you have for the help desk? The primary purpose of the analysis you have just completed is to prevent the misinterpretation of data. You can never assume that the end user will be able to interpret the data the way it should be understood. It is up to you. Provide concise examples to back up your recommendations. Never simply provide a raw data dump. Instead, seek to provide quantitative analysis! Submit your report and Excel workbook in the Project 4: Quantitative Analysis assignment folder below. Check Your Evaluation Criteria Before you submit your assignment, review the competencies below, which your instructor will use to evaluate your work. A good practice would be to use each competency as a self-check to confirm you have incorporated all of them. To view the complete grading rubric, click My Tools, select Assignments from the drop-down menu, and then click the project title. • • • • • • • • • 1.1: Organize document or presentation clearly in a manner that promotes understanding and meets the requirements of the assignment. 1.2: Develop coherent paragraphs or points so that each is internally unified and so that each functions as part of the whole document or presentation. 1.4: Tailor communications to the audience. 1.5: Use sentence structure appropriate to the task, message and audience. 1.6: Follow conventions of Standard Written English. 3.1: Identify numerical or mathematical information that is relevant in a problem or situation. 3.2: Employ mathematical or statistical operations and data analysis techniques to arrive at a correct or optimal solution. 3.3: Analyze mathematical or statistical information, or the results of quantitative inquiry and manipulation of data. 3.4: Employ software applications and analytic tools to analyze, visualize, and present data to inform decision-making. 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0 0 3 1 3 1 1 3 3 3 1 1 2 3 2 3 3 0 0 0 3 1 3 3 0 1 3 0 0 3 0 7 13 0 1 1 0 0 2 14 7 1 26 3 0 1 12 5 3 0 9 2 6 1 3 6 8 0 19 0 2 2 4 0 0 6 17 1 5 0 2 18 10 1 7 0 2 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 922 525 1817 267 531 1859 469 1315 1174 339 1847 1907 1764 1646 2 1506 809 176 456 170 1859 1730 1980 89 1397 1909 109 1058 180 447 342 437 555 326 1199 572 1903 791 559 1857 721 1594 1429 1669 1356 564 1039 Regular Executive Management Regular Management Management Regular Management Executive Regular Management Executive Management Regular Regular New Employee Executive Management New Employee Management Management New Employee Executive New Employee New Employee Regular Executive Executive Executive Management Executive New Employee Regular Regular Regular Regular New Employee Executive New Employee Regular New Employee Management 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47 50 11 32 33 38 40 24 Software Access/Login Systems Access/Login Systems Systems Software Systems Software Access/Login Systems Systems Access/Login Access/Login Access/Login Software Access/Login Hardware Access/Login Access/Login Software Systems Systems Access/Login Systems Systems Systems Access/Login Systems Hardware Access/Login Systems Software Hardware Access/Login Systems Access/Login Hardware Systems Hardware Access/Login Software Hardware Systems Systems Access/Login Software Request Request Issue Issue Issue Request Request Issue Issue Request Request Issue Request Request Request Request Request Issue Request Request Request Request Request Request Request Request Issue Request Request Request Request Request Request Issue Request Request Request Issue Issue Issue Request Request Request Request Issue Issue Request 2 3 2 2 3 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 1 3 0 2 3 3 0 0 3 1 0 1 2 3 1 2 1 3 0 0 3 1 2 0 3 0 0 0 1 0 3 2 3 3 3 1 2 0 1 3 0 3 3 3 0 3 0 6 0 7 6 5 1 1 0 5 2 0 0 0 8 0 33 0 0 12 6 5 0 7 11 6 0 6 11 1 5 5 6 0 18 0 5 2 7 0 3 10 7 2 0 5 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 885 1326 246 459 1046 1609 932 259 657 42 963 1740 556 1817 1011 1067 1226 299 540 1936 243 1786 1382 1045 943 233 754 775 462 1068 1558 590 990 1395 463 1854 1572 1879 270 546 1797 703 1845 1552 214 160 1813 Management New Employee Executive New Employee Regular Executive Executive New Employee Executive Regular New Employee Management Executive Management Regular Management Regular Regular Regular Regular Regular New Employee Management Executive Management Regular Regular Regular New Employee Regular Regular Executive Management Regular Regular Regular Regular Management New Employee Management Regular Regular Management New Employee Management Regular New Employee 12 35 45 45 46 24 20 16 25 12 4 40 37 19 38 32 14 1 24 21 17 8 34 14 20 33 30 47 45 8 29 46 33 1 42 3 32 23 48 5 44 18 48 30 7 45 42 Access/Login Software Access/Login Systems Software Hardware Systems Systems Systems Systems Hardware Access/Login Software Systems Access/Login Software Software Systems Systems Hardware Systems Software Access/Login Access/Login Systems Software Software Access/Login Access/Login Access/Login Access/Login Access/Login Systems Hardware Access/Login Systems Software Access/Login Software Access/Login Systems Systems Systems Access/Login Access/Login Systems Systems Request Request Request Request Request Request Request Request Request Issue Request Request Request Request Request Request Issue Request Request Request Request Request Request Request Request Request Request Request Request Request Issue Issue Request Request Request Request Request Request Issue Request Issue Issue Issue Request Request Issue Request 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 3 2 2 3 1 3 1 3 0 0 1 3 2 1 0 3 2 1 2 3 3 0 0 2 0 3 3 3 3 0 0 3 1 3 0 3 1 3 2 0 3 1 3 3 2 1 2 3 1 0 0 6 0 5 12 11 26 14 23 1 31 0 3 7 0 3 5 15 10 10 9 7 0 0 10 6 7 0 1 1 0 0 7 26 0 14 11 0 2 0 1 8 3 0 0 3 6 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1549 1365 1762 1392 1673 178 1669 780 1068 919 526 1560 688 1918 506 1440 429 316 98 337 597 827 1389 790 1846 935 597 1141 1367 892 1224 861 1584 694 608 1038 1230 1655 800 1088 582 1931 1860 864 906 391 610 Regular Regular Regular New Employee Executive Regular Regular Management Regular Regular Executive Regular New Employee Executive Regular Regular Executive Executive Regular New Employee New Employee Regular Regular Executive Regular Regular New Employee Management New Employee New Employee Management Executive Regular 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6 0 10 5 7 2 0 7 4 18 0 0 0 11 3 3 0 6 0 0 19 24 14 1 5 1 20 1 5 8 0 0 0 4 34 9 3 0 8 1 10 1 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 253 1583 610 1636 1087 1651 852 1202 287 1308 1032 852 1260 586 1556 580 1987 735 601 751 194 1520 1556 328 539 549 1396 720 1749 527 455 1001 1553 18 363 171 797 1098 614 570 1846 1405 712 1646 1302 279 470 Management New Employee Regular Executive Management Regular New Employee Management Executive Management New Employee New Employee Management Executive Executive Management New Employee Regular Regular Regular Executive Executive Executive Regular Management Executive Executive Executive Regular Regular Regular Management New Employee New Employee Management Executive Regular Regular Regular Regular Regular Regular Executive Regular New Employee Regular 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3 2 1 0 0 3 3 1 0 3 1 3 0 2 3 3 0 0 1 0 3 3 5 12 0 10 3 7 29 24 13 11 14 7 0 7 7 0 0 18 10 0 2 20 19 0 0 26 8 0 1 6 4 6 22 1 30 0 8 13 8 5 2 0 2 5 5 5 0 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638 1639 1640 1641 1642 1643 1944 679 1542 348 895 1058 1535 1067 454 1094 1228 1291 1718 1938 188 1021 995 1626 1152 1280 1401 477 544 1093 914 1867 1152 1988 124 1342 1441 1781 1883 1058 1622 1090 363 1952 425 621 1008 116 1925 466 985 460 878 Regular Regular Executive New Employee Management Executive Regular Management Executive New Employee Executive New Employee Executive Regular Regular Regular Executive Regular Executive Executive Regular Management Regular Regular New Employee Management Executive New Employee Management Management Management Executive Regular Executive Regular Executive Management New Employee Regular 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