ITECH7406 Business Intelligence and Data Warehousing, SEM1, 2020 Assignment #2 (Team Presentation) & #3 (Team Research Report) 2. Team Presentation (10%) Duration: 15 Minutes Due: In Scheduled...

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ITECH7406 Business Intelligence and Data Warehousing, SEM1, 2020 Assignment #2 (Team Presentation) & #3 (Team Research Report) 2. Team Presentation (10%) Duration: 15 Minutes Due: In Scheduled Tutorial (Week 10) 3. Team Research Report (10%) Word Count: 3500 words Due: Friday, 29 May 2020 - 17:00 (Week 11) There are new and exciting developments that are taking place in the Business Intelligence literature that is constantly shaping the use and implementation of Business Intelligence and Data warehousing tools and applications in organizations. The objective of this assessment is to: (i) Provide a forum for students to investigate the practice, approaches and understanding of business intelligence as it is being applied in the real world to realize organizational objectives. (ii) Allow students to show innovation and creativity in applying SAP BusinessObjects Lumira, SAP Predictive Analytics, or any other analytical tool and designing useful visualization for chosen datasets. Students are expected to select a data set of choice and through analysis of the selected dataset and research into the literature complete the following Assessment tasks. Assessment Task 2 (Team Presentation) & Task 3 (Team Research Report) Task #2: Team Presentation Duration – 15 Minutes Due – In Scheduled Tutorial (Week 10) Task #3: Team Research Report Word Count – 3500 words Due - Friday, 29 May 2020 - 17:00 (Week 11) Students form a team of 3 to 4 members to complete the Task #2 and Task #3. Each team has to develop innovative analytics and visualization of the selected datasets. Each team will give a presentation and submit an academic research report of 3500 words that draws on the chosen datasets, to demonstrate their understanding on the following Business Intelligence areas. “With the rising complexity of the business intelligence environment, the identification of trends and market developments is a key factor in effective decision-making. It is increasingly important to use the latest technologies and approaches in order to cope with digitalization and market competition”. Assessment Tasks #2 & #3 (Team Presentation and Research Report) a. The team report must address the following: b. Include a discussion about Two (2) most important BI Trends (e.g. Data quality/Master data management, Data discovery/Visualization, Self-service BI etc.) c. Describe the impact of BI and Data Analytics specifically in the novel and interesting domains of Government, Banking, Manufacturing, Sports, Healthcare or Cyber Security etc. d. Each team only required to choose Two (2) domains with Two (2) respective dataset for their research. e. IMPORTANT: For this assignment, selected datasets have to be different than the assignment #1 (Individual Analytic Report). f. Team report must include at least 15 references. Some Datasets/Sources: 1. http://data.un.org/Explorer.aspx 2. http://data.worldbank.org/topic/environment 3. https://data.oecd.org/ 4. http://geodata.grid.unep.ch/ 5. http://open-data.europa.eu/en/data/publisher/eea 6. https://www.data.gov/ General Guidelines Marks would depend on the following factors: 1. Depth of research to illustrate the BI tools/application, chosen 2. Quality of reference provided 3. Quality of overall team presentation and academic report writing. Make sure your follow academic report structure with cover page, introduction, use of headings, subheadings, conclusion sand reference section. Please note that all references must adhere to APA style. You are reminded to read the “Plagiarism” section of the course description. Your essay should be a synthesis of ideas from a variety of sources expressed in your own words. A passing grade will be awarded to assignments adequately addressing all assessment criteria. Higher grades require better quality and more effort. For example, a minimum is set on the wider reading required. A student reading vastly more than this minimum will be better prepared to discuss the issues in depth and consequently their report is likely to be of a higher quality. So before submitting, please read through the assessment criteria very carefully. http://data.un.org/Explorer.aspx http://data.worldbank.org/topic/environment https://data.oecd.org/ http://geodata.grid.unep.ch/ http://open-data.europa.eu/en/data/publisher/eea Team Presentation Weighting: 10% Each team is expected to create and present a 15 minutes overview of their research report. Student Names/IDs: Assessment Criteria Criteria Marks Introduction /1 Contents – integration, comparison, findings, implications and impacts /5 Conclusion /1 Presentation Style e.g. clarity, engagement, confidence etc. /2 Timing (10 minutes) /1 Total /10 General Comments: Team Report Weighting: 10% Student Names/IDs: Assessment Criteria Score Very Good Good Satisfactory Unsatisfactory (0) Layout Information is well Information is Information is Information is organized, well organized, well somewhat organized, somewhat organized, written, with proper written, with proper proper grammar and but proper grammar grammar and grammar and punctuation mostly and punctuation not /1 punctuation are used punctuation. Correct used. Correct layout always used. Some marks throughout. Correct layout used. used. elements of layout layout used. incorrect. Structure Structure guidelines Structure guidelines Structure guidelines Some elements of enhanced followed exactly mostly followed. structure omitted /1 marks Introduction Introduces the topic Introduces the topic Satisfactorily Introduces the topic of the report in an of the report in an introduces the topic of the report, but extremely engaging engaging manner of the report. omits a general manner which which arouses the Gives a general background of the arouses the reader's reader's interest. background. topic and/or the interest. Gives a Gives some general Indicates the overall overall "plan" of the detailed general background and "plan" of the paper. paper. background and indicates the overall /1 indicates the overall "plan" of the paper. marks "plan" of the paper. Discussion of All topics discussed Consistently detailed Most topics are Inadequate topics in depth. Displays discussion. Displays adequately discussion of issues deep analysis of sound understanding discussed. Little/no issues with no with some analysis of Displays some demonstrated irrelevant info. issues and no understanding and understanding or irrelevant information analysis of issues. analysis of most /4 issues and/or some marks irrelevant information. Conclusion An interesting, well A good summary of Satisfactory summary Poor/no summary of written summary of the main points. of the main points. the main points. the main points. A good final comment A final comment on A poor final comment An excellent final on the subject, based the subject, but on the subject and/or comment on the on the information introduced new new material subject, based on the provided. material. introduced. /1 information provided. marks Referencing Correct referencing Mostly correct Mostly correct Not all material (APA). All quoted referencing (APA). All referencing (APA ) correctly material in quotes quoted material in Some problems with acknowledged. and acknowledged. quotes quoted material and Some problems with All paraphrased &acknowledged. All paraphrased material the reference list. material paraphrased material Some problems with acknowledged. acknowledged. the reference list. /2 Correctly set out Mostly correct setting marks reference list. out reference list. SubTotal /10 marks
Answered Same DayMay 22, 2021ITECH7406

Answer To: ITECH7406 Business Intelligence and Data Warehousing, SEM1, 2020 Assignment #2 (Team Presentation) &...

Payal answered on May 26 2021
136 Votes
BUSINESS INTELLIGENCE &
DATA WAREHOUSING
TABLE OF CONTENTS:
1. PURPOSE
2. INTRODUCTION TO TABLEAU
3. DOMAIN SELECTION
3.1 AUDIT ANALYTICS
    3.1.1 DATA ANALYSIS
3.2 HEALTHCARE ANALYTICS
    3.2.1 DATA ANALYSIS
4. ROLE OF BI TRENDS
4.1 MASTER DATA MANAGEMENT
4.2 DATA VISUALIZATION
5. IMPACT OF DATA ANALYTICS & BUSINESS INTELLIGENCE
5.1 IMPACT ON AUDIT ANALYTICS
4.2 IMPACT ON HEALTHCARE ANALYTICS
6. CONCLUSION
1.PURPOSE:
The purpose of the assignment is to understand the importance of Business Intelligence & Data Warehousing in Organizations. The basic objective is to get the detail understanding on approaches followed by Organizations & practice followed thereafter in the real world to uncover the hidden challenges & helps in meeting Organizational objectives.
We shall be considering Tableau for our stu
dy
2.INTRODUCTION TO TABLEAU:
Tableau is a powerful data visualization tool used in the Data Analytics and Business Intelligence Industry. It helps in simplifying raw data which in turn can be easily turned into an understandable format., to gain meaningful insights out of the data
The great thing about tableau is its user-friendliness it offers to the users for various analysis. By using Tableau, even a non-technical user can create a customized dashboard. The best feature Tableau are
· Data Blending
· Real time analysis
· Collaboration of data
Over the years the tool has attracted the attention of people from all sectors such as business, researchers, different industries, etc.
Moreover, to promote the product within educational institutions, students at college level, it offers a Tableau student version which is free for the students up to a period of one year. (Anoshin, 2019) (Baldwin, 2019.1)
SAMPLE DASHBOARD:
3. DOMAIN:
Let us understand the concept of Business Intelligence Tool & Data Warehousing in the real world. Here, we are considering 02 domains for our details study –
1) Finance - Audit Analytics
2) Healthcare Analytics – Pandemic Disease (Covid-19)
3.1 AUDIT ANALYTICS:
Every Organizations set up is done based on the primary objective to earn for a living. No matter which type of product or services it is dealing into. To keep the clear visibility of profits & Losses of any Organization & its management, their internal finances is required to be top of the focus criteria. However, any leakage in Financial transaction may lead to closing the shutter of any Organization.
Audit analytics is a novel field where the use of advanced business intelligence tools have helped auditors and the business to gain deep understanding of any abnormality in the business operations of an Organization. Moreover, the use of Business intelligence in audit analytics is biased free and not affected by the subjectivity of the auditor unlike in case of traditional auditing. The use of data analytics has transformed the way how auditing is done and many auditors are finding ways to gain deeper understanding of their clients’ organizations than ever.
Audit analytics plays a very crucial role to design the Standard Operating Procedures (SOP’s) for an Organization. (Murphy, 2015)
SAMPLE DATASET (Audit Analytics):
    Order ID
    Order Date
    Ship Date
    Customer Name
    Segment
    State
    CA-2013-109365
    04-11-2013
    09-11-2013
    Xylona Preis
    Consumer
    California
    CA-2014-115175
    08-08-2014
    13-08-2014
    Matt Collins
    Consumer
    California
    CA-2014-121853
    24-09-2014
    30-09-2014
    Duane Benoit
    Consumer
    California
    US-2014-113201
    01-07-2014
    06-07-2014
    Thomas Thornton
    Consumer
    California
    CA-2013-130267
    20-09-2013
    24-09-2013
    Scot Wooten
    Consumer
    California
    CA-2012-101707
    27-08-2012
    01-09-2012
    Philip Fox
    Consumer
    California
    CA-2014-149076
    15-01-2014
    20-01-2014
    Sean O'Donnell
    Consumer
    California
    CA-2013-112060
    05-12-2013
    10-12-2013
    Kean Takahito
    Consumer
    California
    CA-2012-105347
    24-11-2012
    28-11-2012
    Darren Powers
    Consumer
    California
    CA-2012-135580
    30-12-2012
    03-01-2013
    Clay Ludtke
    Consumer
    California
    CA-2013-109365
    04-11-2013
    09-11-2013
    Xylona Preis
    Consumer
    California
    CA-2012-135545
    24-11-2012
    30-11-2012
    Kunst Miller
    Consumer
    California
    CA-2014-117457
    09-12-2014
    13-12-2014
    Keith Herrera
    Consumer
    California
    CA-2011-118962
    05-08-2011
    09-08-2011
    Chad Sievert
    Consumer
    California
    CA-2014-104647
    24-02-2014
    02-03-2014
    Clytie Kelty
    Consumer
    California
    CA-2014-122770
    14-12-2014
    19-12-2014
    Emily Phan
    Consumer
    California
    CA-2014-118542
    02-12-2014
    06-12-2014
    Clay Cheatham
    Consumer
    California
    US-2013-108455
    03-12-2013
    09-12-2013
    Mike Kennedy
    Consumer
    California
    CA-2014-148320
    04-11-2014
    09-11-2014
    Paul Gonzalez
    Consumer
    California
Sample Image of the dataset considered in case of Health Disease
3.1.1 DATA ANALYSIS:
In this analysis we will be applying the Business Intelligence in the field of audit analytics.
The business case here is to identify the fraud of channel stuffing in an organization on the part of the salesperson. We have considered Superstore sales data that consist of various transaction over the various regions represented by the respective salesperson of that region.
CHANNEL STUFFING:
It is when sales people in an organization officially inflate sales, for the sake of hitting targets. This often stems from the pressure of meeting sales target. In our analysis in order to identify the case of channel stuffing we will consider the case where sale is made to a distributer in last two months of one year and then returned in the first two months of the next year. So, that kind of behaviour we are going to look for into our analysis.
3.1.1.1 Scope -
To study the sales made by the various salesperson and identify the return orders among them, in order to further investigate, whether the return date other particular order id is suspicious or not. Suspicious here means the sales which are made in last two months of one year and then returned in the first two months of the next year.
Conclusion -     
Here we have plot a bar graph, to study the return orders which are falling into the suspicious category. It can be seen from the above analysis that Jack Lebron, a salesperson, has the highest share of suspicious orders which are returned. (Murray, 2013)
3.1.1.2 Scope -
In this analysis we are going to further drill down and filter out the sales person having the suspicious orders of return date.
Conclusion -    
It can be seen from the above analysis that the average of suspicious orders is around $19k, but Jack LeBron, has the around $112K of suspicious returns leaving behind everybody with a great amount.
3.1.1.3 Scope -
To study how the overall sales compared with returned sales overtime.
Conclusion -
We have used a line chart to show the overall sales compared with returned sales overtime. It can be seen from the above analysis that average sales are increasing overtime. It can also be seen that returns are high for the orders made during the end of the years.
Therefore, Jack is definitely an Outlier here, means he as inflated the sales to meet the year end targets.
The analysis which has been conducted above can help the company in knowing the fraud on the part of sales person to inflate the sales for meeting the targets. This is in turn can leverage the decision-making power of the upper management of the company while deciding the appraisal and bonuses of the particular manager, rather than blindly giving the appraisal on the basis of wrong figures.
3.2 HEALTHCARE ANALYTICS:
Healthcare analytics involves collecting and analysing of data in the healthcare industry in order to gain insights for better decision-making. From key areas like medical costs, clinical data, patient behaviour, pharmaceuticals, etc., healthcare analytics can be used on both macro and micro levels to effectively streamline business operations, improve patient care, and lower overall costs.
Healthcare analytics has grown immensely over the past few years. It has empowered the firms operating in the healthcare sectors to take better decisions that align with the business as well as the societal objectives. The use of data...
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