1 | P a g e ITECH1103- Big Data and Analytics Group Assignment – Semester 2, 2018 Worth – 30% ANALYTIC REPORT (20%- Due Week 11 Sunday 11:55pm) and PRESENTATION (10% - Due Week 10 in Tutorial Time)...

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1 | P a g e ITECH1103- Big Data and Analytics Group Assignment – Semester 2, 2018 Worth – 30% ANALYTIC REPORT (20%- Due Week 11 Sunday 11:55pm) and PRESENTATION (10% - Due Week 10 in Tutorial Time) Analytic Report: Learning Outcomes Assessed: A3, K3, K6, and S2: Purpose: The purpose of this task is to provide students with practical experience in working in teams to write a Data Analytical report to provide useful insights, pattern and trends in the chosen/given dataset. This activity will give students the opportunity to show innovation and creativity in applying Watson Analytics and designing useful visualization solutions and predictive solutions for various analytics problems. Group Presentation: Week 10 (Scheduled Laboratory) Learning Outcomes Assessed: K4, A1, A2, V1, V2 Purpose: The purpose of the oral presentation is to provide an opportunity for students to present the results of DATA Analysis and to share this knowledge while practicing their verbal communication skills Project Details: Your task for this analytical project is to use analytical tool (i.e Watson Analytics) to explore, analyze and visualize one of the two given dataset. Your tutor will assign you the dataset. This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2012. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified.Your intended audience is a law enforcement agency’s middle and top middle management. Your primary goal is to provide different and interesting insights in the lights of 20 questions listed below. The dataset could be downloaded from the following link Data Sets: Dataset 1 - https://data.world/mchadhar/chicagocrime-dataset Dataset 2 - https://data.world/mchadhar/dataset-2-chicago-crime https://data.world/mchadhar/dataset-2-chicago-crime 2 | P a g e Data Dictionary: ID - Unique identifier for the record. Case Number - The Chicago Police Department RD Number (Records Division Number), which is unique to the incident. Date - Date when the incident occurred. this is sometimes a best estimate. Block - The partially redacted address where the incident occurred, placing it on the same block as the actual address. IUCR - The Illinois Unifrom Crime Reporting code. This is directly linked to the Primary Type and Description. See the list of IUCR codes at https://data.cityofchicago.org/d/c7ck-438e. Primary Type - The primary description of the IUCR code. Description - The secondary description of the IUCR code, a subcategory of the primary description. Location Description - Description of the location where the incident occurred. Arrest - Indicates whether an arrest was made. Domestic - Indicates whether the incident was domestic-related as defined by the Illinois Domestic Violence Act. Beat - Indicates the beat where the incident occurred. A beat is the smallest police geographic area – each beat has a dedicated police beat car. Three to five beats make up a police sector, and three sectors make up a police district. The Chicago Police Department has 22 police districts. See the beats at https://data.cityofchicago.org/d/aerh-rz74. District - Indicates the police district where the incident occurred. See the districts at https://data.cityofchicago.org/d/fthy-xz3r. Ward - The ward (City Council district) where the incident occurred. See the wards at https://data.cityofchicago.org/d/sp34-6z76. Community Area - Indicates the community area where the incident occurred. Chicago has 77 community areas. See the community areas at https://data.cityofchicago.org/d/cauq-8yn6. FBI Code - Indicates the crime classification as outlined in the FBI's National Incident- Based Reporting System (NIBRS). See the Chicago Police Department listing of these classifications at http://gis.chicagopolice.org/clearmap_crime_sums/crime_types.html. X Coordinate - The x coordinate of the location where the incident occurred in State Plane Illinois East NAD 1983 projection. This location is shifted from the actual location for partial redaction but falls on the same block. Y Coordinate - The y coordinate of the location where the incident occurred in State Plane Illinois East NAD 1983 projection. This location is shifted from the actual location for partial redaction but falls on the same block. Year - Year the incident occurred. Month- Month the incident occurred. Day – Day the incident occurred Updated On - Date and time the record was last updated. Latitude - The latitude of the location where the incident occurred. This location is shifted from the actual location for partial redaction but falls on the same block. Longitude - The longitude of the location where the incident occurred. https://data.cityofchicago.org/d/c7ck-438e https://data.cityofchicago.org/d/aerh-rz74 https://data.cityofchicago.org/d/fthy-xz3r https://data.cityofchicago.org/d/sp34-6z76 https://data.cityofchicago.org/d/cauq-8yn6 http://gis.chicagopolice.org/clearmap_crime_sums/crime_types.html 3 | P a g e This location is shifted from the actual location for partial redaction but falls on the same block. Location - The location where the incident occurred in a format that allows for creation of maps and other geographic operations on this data portal. This location is shifted from the actual location for partial redaction but falls on the same block. You are expected to present the data findings in a visual forms (i.e., charts and graphs). This is a group assignment. You will complete it with your team (max 3 members enrolled in the same laboratory). It is expected that each team member will contribute equally in the project. Each team will turn in one joint document and give a joint presentation in Timetabled Laboratory class in Week 10. In addition, each individual team member will write a short reflection as part of the report. You will receive feedback on the draft about presentation choices, content, analysis, and style. The Questions Your job is to examine one of the available datasets and present it in a set of informative graphs and text by answering the following questions. Guided Questions for Dataset 1 1. How many total number of reported crimes? 2. How many different number of reported crimes types? (Primary type) 3. Provide a list of top 21 location descriptions with respect to crimes. 4. Provide a list of least 10 location descriptions with respect to crimes. 5. What is the top three most common primary type? 6. What are the three least common primary types? 7. How many years of Years of reported crimes is in the data file? 8. How many number of reported crimes were logged every year in December? 9. Which year generated the most reported crime in Chicago? 10. Which month generated the most reported crime in Chicago? 11. How many number of reported crimes whether an arrest was made? (Arrest) 12. How many number of district in this dataset? 13. What are the top 3 districts in terms of reported crimes? 14. What are the least 3 districts in terms of reported crimes? 15. What was the primary type that reported most crimes from district “8” in 2014? 16. How many number of domestic reported crimes made in Chicago? 17. How many domestic number of reported crimes were made in 2012 to 2014? 18. Which day is the busiest day of the week in terms of committed crimes? 19. Which location description has the most number of crime reported on Weekends? 20. Which location description has the least number of crime reported on weekends? Guided Questions for Dataset 2 1. How many total number of reported crimes? 2. How many different number of reported crimes types? (primary type) 3. How many location descriptions of reported crimes? (location description) 4 | P a g e 4. What are the top three most common primary type that reported crimes ? 5. What are the three least common primary types? 6. How many years of Years of reported crimes is in the data file? 7. How many number of reported crimes were logged in the last week of the dataset? Considered (11 of January 2017 , 18th of January 2017) 8. Which year generated the most reported crime in Chicago? 9. Which month generated the most reported crime in Chicago? 10. How many number of reported crimes whether an arrest was made? (arrest) 11. How many number of district in this dataset 12. Which District in Chicago reported most crimes in the last year? (last year of dataset) 13. Which District in Chicago reported least crimes in the last year? (last year of dataset) 14. What was the primary type that reported most crimes from district “8” last year? 15. How many number of domestic reported crimes made in Chicago? 16. How many domestic number of reported crimes were made over the past month? (last year of dataset) 17. Which location description has the most number of crime reported in Chicago? 18. Which location description has the least number of crime reported in Chicago? 19. Which location description has the most number of crime reported on Weekends? 20. Which location description has the least number of crime reported on weekends? Task 1- Background information Write a description of the selected dataset and project, and its importance for the firm. Information must be appropriately referenced. [1 Page] Task 2 – Reporting / Dashboards For your project, perform the relevant data analysis tasks by answering the above questions and, identify the visualization and dashboards you need to develop for the operational manager of the indicated firm. [2-3 Pages] Task 3 – Advanced Insights: In addition to the guided questions, it is expected to provide at least five (5) insights of the data. These insights will be judged in terms of quality and complexity. Task 4 – Research Justify why these BI reporting solution/dashboards are chosen in Task 2 (Reporting / Dashboards) and why those data sets attributes are present and laid out in the fashion