As a data scientist in an organization you frequently find yourself in a couple of situations:

Thinking of data science as merely a technical profession, like programming, may take you away from your goals. Focusing on the usability of mathematics for data science before jumping into full-fledged math courses will save you a lot of time.

I wrote this blog post because I made a few mistakes while starting…

The history of F1 motor racing and the use of telemetry as a way to monitor car setup and performance dates back to the 80s. The first electronic systems were installed onboard the car, collected information for only one lap and the data were then downloaded when the car was back in the garage. The explosion of computing capabilities, in the 90s, contributed to the growth of intelligent data usage in the F1 and the…

Walking by the hottest IT streets in these days means you've likely heard about achieving Streaming Machine Learning, i.e. moving AI towards streaming scenario and exploiting the real-time capabilities along with new Artificial Intelligence techniques. Moreover, you will also notice the lack of research related to this topic, despite the growing interest in it.

If we try to investigate it a little bit deeper then, we realize that…

Summary:  A little history lesson about all the different names by which the field of data science has been called, and why, whatever you call it, it’s all the same thing.

A little reminiscence, or for those of you who are only recently data scientists, a little history lesson. 

Our profession of…

By 2027, the big data market is estimated to grow to USD 103 billion. And by 2022, the global big data and analytics market is predicted to grow to USD 274 billion, statistics backed by Statista.

The scarcity of talent in the big data industry is being wooed by hefty pay packages, but only to those with extensive knowledge in big data tools and technologies.…

Business intelligence is important for every business. But, there is a lot of confusion about business intelligence.

This is mainly because BI has been defined in different ways. So, we thought what’s better than talking about business intelligence. We dived into the history pages and compiled a list of definitions and examples that will help you understand this concept better.…

Business analytics is here to stay, and most ventures are wrapping their heads around the idea. Numerous data gets collected from various interactions among clients and potential prospects; Big data is referred to as the complex humongous data. It is not a new fad in the analyst industry. Organization requires making top-notch decisions using big data as an essential component in…

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 systems. Data analytics provides greater efficacy and higher hit rate than traditional investigative methods – and now can even be performed using only public…

Cybersecurity Data Science (CSDS) is a rapidly emerging profession focused on applying data science to prevent, detect, and remediate expanding and evolving cybersecurity threats. CSDS is increasingly formally recognized as a cybersecurity job specialty, for instance in the NIST NICE Cybersecurity Workforce Framework.

A proposed CSDS definition derived from…

by Vic Diloreto, Director, Software Products, Elder Research

The Risk Assessment Data Repository (RADR) is a powerful risk analytics platform used to enhance productivity in the investigation of fraud, waste and abuse. This server-based, data analytics product  fuses data from…

Q1. Is MSc in Data science/Data Analytics same as ML/AI as some universities don’t have AI but Data Science?

Q2. I am interested in MS Data Science and not MS Analytics as the later is not technical in nature. Are MS Data Science and MS Data Analytics the same?

Q3. How to Choose Between a Master’s in Data Analytics vs Business…

By Stefan Stoyanov, Business Analytics & Research Intern at Boemska

I started my MSc Business Analytics course at theh University of Surrey almost one year ago. I had no prior experience in Machine Learning or data science. Before, I used to develop and manage EU projects…

Of late, a buzzword in marketing and analytics circles is CDP or Customer Data Platform. Chief Marketing Officers now have this new weapon in their arsenal to serve customers in an even better, faster and more granular manner. 



A CDP is a “data unifying software”. Adding it on top of your martech stack helps manage your…

Note: This blog was written by Dr. John Elder and was originally published on www.elderresearch.com/blog.

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Elder Research has solved many challenging and previously unsolved technical problems in a wide variety of fields for…

Note: This blog was written by Dr. William Goodrum and originally posted on www.elderresearch.com.

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It has become common to talk about data being the new oil. But a recent piece from …

Data is the new fuel- it drives businesses towards exponential growths. It has the power to transform operational and add intelligent insights with its immense potential. The key, however, lies with understanding data and its insights.

Logistics, like other domains, can also leverage from the several advantages of data. It all begins with what to do with the collected data. Data Science will come into the picture with its amalgamation of statistical &…

If you are a recent graduate or someone preparing for your first data scientist position, then here are some tips to help you ace your interview!…

Python is the most loved, dreaded, and wanted programming languages by most developers, according to StackOverflow survey.  Popular among most professional software developers, Python was ranked the world’s seventh popular programming language.

A study by PYPL Popularity of Programming Language Index (a study that monitors the frequency of searches regarding the popular programming languages to learn) predicted that it showed that there was a growth of 17.1% during the last…