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Domestic Violence can be defined as violence between any family members.

This blog post has been written as part of the assignment for Business Analytics studied at Victoria University. Getting the practical hands-on experience of SAP products in this university has always been the best part of learning experience. We are very grateful to our lecturer Dr Paul Hawking who helped in understanding the attributes of a good visualizations and Dr Scott Bingley for helping us to fetch data and cleanse it for good visuals.

This blog post will help you understand what can be done using the SAP Lumira (Both Desktop and Cloud) when it is used as an analysis tool to analyse data. As part of our assessment we were asked to analyse the situation of domestic violence in Australia. But due to the lack of clear usable data and the vast and diverse information available on the internet we decided to analyse the data only for New South Wales and analyse six randomly selected suburbs of NSW with some good visualizations using SAP Lumira. The six suburbs which have been laid emphasis on are Shellharbour, Shoalhaven, Singleton, Snowy river, Strathfield, Southerland Shire.

Domestic violence has always been an important aspect of concern. Section 4(1) of the Crimes Act 1900 (NSW) defines domestic violence as a personal violence offence committed against a person who is currently or was previously linked to the perpetrator in the following ways:

• married, in a defacto or intimate personal relationship;

• living in the same household or residential facility;

• In a relationship involving his or her dependence on the perpetrator;

• A relative.

Domestic assaults may range from pushing, slapping and threats of violence to use of weapons such as knives or guns, and may result in little or no physical injury through to serious wounding or even death. Domestic assault, like any other physical assault is a crime punishable by law.

What are we doing?

Method:

  • The data for this assesment was drawn from three sources:

          1. The NSW Police Force’s Computerised Operational Policing System (COPS) database;

          2. The Bureau of Crime Statistics and Research’s (BOCSAR) Criminal Courts database; and;

          3. BOCSAR’s Re-offending Database, ROD (for further explanation of ROD, see Hua & Fitzgerald, 2006).

  • Data was cleansed from the list of crimes to only Domestic Violence related crimes in a separate spreadsheets.
  • Data was uploaded to SAP Lumira Cloud to test for visualizations. However, for this assessment SAP Lumira Desktop version was used for Story Building.
  • Each piece of data was carefully examined and appropriate visualizations were made using Bar Charts, Column Charts, Line Charts, Pie Charts, Heat Charts and Geo Choropleth Charts.
  • The “Compose” option in SAP Lumira (Desktop Version) was helpful in combining and comparing different aspects of the data sets and making meaningful info-graphics.
  • The story developed was then converted into a video and recorded for sharing.

STATISTICS AND RESULTS:


Some of the key visualizations of our findings are:



Visualization #1

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Description : This Visualization shows the suburbs that are highlighted darker have been more affected in NSW from 2009-2014.


Visualization #2

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Description : This Visualization shows the number of domestic violence incidents of top 20 suburbs that have been affected most in NSW in the year 2010 By Remoteness



Visualization #3

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Description: This visualization shows the Indigenous and non-indigenous status of the aforementioned six suburbs. The former chart is about offenders and later charts is for Victims of Domestic Violence.

Visualization #4

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Description: This Visualization depicts the alcohol related incidents that led to domestic violence and describes the Percentage related to alcohol related offences with respect to non-alcohol related domestic assaults.

Visualization #5

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Description: This Visualization shows area of premise where the domestic violence related assaults happened. So we can conclude that, Residential Premises contributed majorly to domestic violence.

Visualization #6

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Description: This former visualization helps us understand which months have higher rate of domestic violence related assaults and the later chart shows the statistics of the suburbs in relation to the months.



Visualization #7


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Description : This bar chart and line chart further drills down for the incidents that happened by day of week and time of occurrence. This graph clearly shows that domestic violence related assaults increases on weekends and are at peak in the evening time ( 6 pm – 12 am)




Issues faced in development of this assignment


Futhermore, some of the issues we encountered were:

  • There is no centralized system for getting data in a standard format.
  • Searches made on the pool of internet was complex and time-consuming
  • SAP Lumira needs a fast processor and RAM, sometimes becomes unresponsive and create time-lags.
  • Cleansing of data could take days depending upon complexity.



Thus, we can conclude that every day in this world heart breaking and traumatic incidents of domestic violence are happening. We need to raise voice for the injustice and be a voice for the thousands of unheard people. Stand by with those victims whose voices are in silence with fearful eyes. Governments and councils at every level need to address these concerns for the betterment of humanity and the generations to come. Let peace and harmony prevail.


Thank You


Pranav Gulati







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