Detecting Hidden Fraud Risk from Public Data
by Hudson Hollister Detecting which of the federal government’s millions of contracts most likely involve fraud used to require insider access to agencies’ IT system...
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Comparing Data Sets in One Picture
Which statistical method you use to compare data sets depends on two main factors: your overall goal and the type of data you have. Parametric data means that you know t...
How to Become a Data Scientist on your Own
Originally posted by Zeeshan Usmani in May 2015. Big Data, Data Sciences, and Predictive Analytics are the talk of the town and it doesn’t matter which town you are r...
The Role of Big Data in Customer Software Development
The process of software development is rapidly evolving with the emerging new technologies being introduced in the field. In order for any software development service to...
Why You Should Integrate Big Data into Your .NET solutions
As the world continues to collect more and more data with every passing second, it is only understandable that we would need tools that would help us make sense of all th...
Why Every Data Scientist Needs A Data Engineer
This article was written by Laurel Brunk. Data scientists spend most of their time (up to 79%!) on the part of their job they hate most. The Role of a Data Scientist On...
What is the role of CDO, How Do They Help in Structuring Data Functions?
The explosion of data in the world – right from the data collected from the cameras to the data gathered from visitors’ actions on websites – is staggering. With ne...
5 Common Issues that Wreck Database Security and How to Solve them
With data growing at its highest rate ever, cyberattacks and digital warfare are on the rise to get hold of any crucial data. The malicious actors primarily target the da...
Federated Machine Learning – Collaborative Machine Learning without Centralised Training Data
Like a failed communist state traditional machine learning centralises training of a model on a single machine. Centralising data in a single central location is not alwa...
On Being a 50 Year Old Data Scientist
At the time of writing, I’m a 52 year-old working in the fields of mathematics and data science. In mathematics, that makes me well-seasoned (and probably well-tenu...