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Big data analytics helps businesses analyze and examine large amounts of data. The process involves hidden patterns, correlations, and provides deep business insights to make an appropriate business decision. Basically, organizations have realized the strengths of big data analytics and its features. Businesses want to be more objective and data-driven and so they are embracing the power of data and technology. In the government and public sector, big data analytics are also playing a major role in crime detection and prevention. Many government agencies have already adopted big data analytics as a major tool for data and forecasting analysis.
Organizations have invested in big data analytics and are expected to make quick and agile business decisions to remain competitive. In this article, we are going to explain the benefits of big data analytics in the government sector to detect crime and prevent it. Keep reading to find out more.

What data can be used to predict crime?

The data that can be used for analysis such as shootings, murders, and robberies, patterns, and trends in the behavior of these offenses can be noted below which in turn will help reduce these offenses.
Reports of these crimes can be used for analysis and records for a week. These reports can later be used to detect patterns in a region for one year.
In addition, data and the conditions associated with it, like prisoners on parole, can also be usefully interpreted using analytics. This data helps state police employees to report crime and add staff to the system to obtain real-time information for effective crime prevention.
The data is also generated from CCTV systems, which come in advance analysis to improve response time public safety incidents. Analytics has the potential to enable the police to achieve a truly preventive approach, as it can help to gain new understanding from the data and identify and identify suspicious behaviors and activities.

Crime Management Centre

predicting crime

Preventing Policing: Preventing policing strategy tracks criminals, focuses on areas where crime is most likely to occur and informs resources that help prevent crime and react quickly to incidents.

Incident Detection: This strategy includes gunshot spotter, video surveillance, etc., which generate data that can be used to inform the responding unit.

Incident Reception: Responding teams use technology to generate incident data such as fingerprint data, video evidence, etc., which can be used in real-time-management cases.

Incident Response: Incident feeds data analytics tools that inform case assignments, provide a view of an entity and non-explicit relationships, and generate strategic leads.

Incident investigation and clearance: This data has been collected to generate crime trend analysis, hot spot detection, and data visualization.

Crime trend analysis: This data is collected for decision making, strategic deployment strategies, and planning strategies.

Strategic and operational planning: Determine preventive policing strategy by measuring impact and success rate.

Determine crime patterns

The goal of big data analytics is to automatically detect patterns of crime. Amid a large set of crimes that occur every year in a major city, it is challenging, time-consuming, and labor-intensive for crime analysts to determine which are committed by a single person. If automated, data-driven tools to detect crime patterns are provided to help analysts, these tools can help police better understand crime patterns, allowing more accurate estimates of past crimes and the suspicion of suspects may increase. To do this, we propose a pattern detection algorithm called a series finder, which extends a pattern of detected crimes from a database starting with the “seed” of some crime. The series finder incorporates the general characteristics of all patterns and unique aspects of each specific pattern and gives promising results on the value of a decade of crime pattern data collected.

predicting crime

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There are several benefits of big data analytics in local and state governments, some of which are listed below:

Decision-Making Improvement:

Today many data analytics tools and technologies are available to process the data generated in real-time, making organizational decisions more quickly and efficiently.

Improve the organization’s goal results:

Big data produces the advantage of being able to predict results and model scenarios based on data.

Identify and reduce inefficiencies:

Big data analytics lets local councils and state agencies understand the mistakes they have made and where they have taken the wrong steps in the past.

Remove fraud and abuse

The biggest benefit of big data analytics in the public or government sector is to eliminate fraud and misuse. By identifying anomalies, organizations can get rid of internal waste.

Reducing crime and security threats

In government departments such as the Ministry of Police and Emergency Services, big data helps uncover crime patterns and illegal activities that pose a specific threat to the community. Big Data also helps the team collaborate to fight crime and detect threats in local territories.

Maintains transparency in service

Proper handling and processing of big data will allow local councils to make data available to the public and private sectors. Processing and sharing data will allow government agencies to provide information as a service, be it online tax records, census information, weather data, or financial reporting

Conclusion

Big data analytics with its use are helpful in various functioning in society. It has proved useful for fighting against crime. Government employees and police can solve these crimes accurately and also prevent them by analyzing the data of crimes. Analytics helps in improving the performance of the government employee and with better results.

Abhishek Sharma

Abhishek Sharma

Software Developer

Abhishek is working as a Web Graphics Designer at EzDataMunch. He is involved in Maintaining and enhancing websites by adding and improving the design and interactive features, optimizing the web architectures for navigability & accessibility and ensuring the website and databases are being backed up. Also involved in marketing activities for brand promotion.

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