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These Data Analysis Projects are Gaining Attention   Featured

These Data Analysis Projects are Gaining Attention    Markus Spiske

Data analytics projects can be challenging to many organizations, especially those entering the murky waters of data analysis for the first time. While you may think data projects need to be complex or showy, that is not always the case. Rather, the most important thing you should do is demonstrate your skills using data sets that interest you. The good news is that any organization, regardless of the time they have spent, is that data is everywhere, and you need to know where and how to find it and what to do with it.

As you seek to use data analytics to the advantage of your business, here are a few data analysis projects that are gaining attention. But first, there are two things that you need to set up before you can succeed in analysis. One of them is cloud computing. Moving data to the cloud has substantially levelled the playing field among the organizations. Furthermore, it gives users the power to use cutting-edge services offered by companies like Google, Amazon and Microsoft. The second is to establish parallel computing distributed cluster servers to increase memory and storage capacity.

Below are some of the projects that are gaining attention.

  1. Fraud detection projects

Even with the advancement that we presume we have made in detecting and solving fraud, hackers still find a way to get into the systems and steal sensitive information or even money. This is especially the case in text messages, emails, financial systems and communication platforms. Fraud detection is a useful tool for identifying the issues and addressing them quickly. However, this cannot be okay without the right data analysis. Big data analytics projects geared towards bolstering fraud detection are gaining momentum.  

  1. Crime prediction

Like fraud detection, big data projects aimed at predicting fraud are gaining ground. This technology uses machine learning to predict and detect crimes. Machine Learning algorithms analyze crime data, subjects and locations, and descriptions of the perpetrators. Big data is used to train models to improve machine-learning capabilities to predict crime. In metropolitan areas, systems are used to monitor traffic to ensure everything flows as efficiently as possible and to report any bottleneck.

  1. Predicting and simulating traffic

Big data projects focused on simulation and prediction of traffic in real-time have proven beneficial in many ways. Traffic simulation has been proven to be successful in models. However, predicting route traffic is a long-standing issue. It is a complex project that requires vast volumes of data, involves high latency and has cost implications.

  1. Nuclear physics and data analysis

While the world we live in today may appear simple, it is a complex place from the big data point of view. Companies like CERN regularly release vast amounts of data for analysis and research to the public. This data is diverse and captures many dimensions, each with various data points. The field of nuclear physics is one of the beneficiaries of big data technologies. These technologies are used to analyze large data volumes. With big data analysis projects, the field of nuclear science has seen much improvement in university research and made institutions competitive.

  1. Employee salary data analysis

One of the biggest ways to understand how an organization or a city works is to analyze the salaries of staff residing in it. This will provide evaluation criteria for the management to understand how individuals are paid. A close look at the employees and their salaries shows the on-demand jobs, and the job offers with the highest compensation packages. This helps job applicants get an idea regarding which jobs will give them better pay.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

scottkoegler.me/

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