Pactera - City of Bellevue Crime

Leverage Power BI application to connect and source City of Bellevue crime data from their public website for a full comprehensive analysis of their series of statistical crime publications by detailing specific offenses and outlining trends that can help better understand crime threats locally.

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City of Bellevue Crime

Power BI Desktop and Power BI Online Services were leveraged to create this powerful crime analysis dashboard for City of Bellevue, WA. The exercise involved publicly available web sourced content that is published by Socrata (https://bellevue.data.socrata.com/Safe-Community/Crime-by-Reporting-District/7ha4-phf5) for years 2014 and 2015.

City of Bellevue has recently made available a host of public data sets which includes crime data collected by law enforcement by capturing more detailed information on each single crime occurrence. Today, the City of Bellevue website makes the raw data available for crime rates at different crime categories providing basic resources to analyze and visualize the data. But, there are no readily available reports which provides quick insights to the key indexes of crime data.

Leveraging Power BI is a great solution to explore this raw data and show the key insights to the audience. By Consuming crime statistics from the City of Bellevue public website (http://data.bellevuewa.gov) and compiling the volume and rate of crime offenses, we are able to explore number of crimes at different crime categories and compare the incident volumes across years, quarters for different crime categories. By applying some creative methods to extract and visualize data, we created calculated measures to display the average time that it took for incidents to get reported from the actual occurrence of the event. This view now allows users to glean some interesting patterns regarding the delay in reporting incidents like ID theft. Power BI Can do even more by using the drill down and drill through features, we can see how incident volumes are distributed across different days of a week in each year on a high level and further we can drill through to each quarter. At a glance, we can easily tell that majority of the incidents were occurred on Fridays in both the years, but when you drill through each quarter then we can observe the number of incidents reported on Mondays in 2014 Q2 and Mondays & Tuesdays in 2014 Q4 were also more apart from Fridays. Using Power BI cross filtering capability, we can narrow down to the details and outline the trend presented visually impactful.

In Summary, Power BI delivers robust visualizations and an ease of implementation that made analyzing the Crime statistics a snap!

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