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R alternative for SPSS?

Introduction to R-scripting for market researchers and data analysts

R alternative for SPSS?

Eric van Velzen
Posted on 14 March 2017 in
by Eric van Velzen
4 min

Nebu together with Dutch MOA and British MRS has launched a series of R-scripting training designed for market researchers and data analysts. 

About the training

Nebu officially launched a series of R-scripting courses. The training is designed for market researchers, and data analysts experienced with SPSS, looking for automation of research projects, and broader data-processing and analytical capabilities to make their projects more efficient.

At Nebu we have noticed a huge increase in the usage of R in the Industry. To support Market Researchers, we have built Nebu Data Hub, an R-based data science and data management platform and reached out to MOA and MRS to together increase the knowledge of R in the market, explained Nebu's CEO, Eric van Velzen. 

When and where?

The first training events will take place in March 2017 in Amsterdam and London. You can still 1.2.pngregister for the training on 20th of March in the UK. The Dutch edition, held on 9th of March was fully booked. Due to popular demand, MOA has just announced an additional training day in Amsterdam on 25th of April 2017, and it is open for registration. 

Learning outcomes

During the training, Joris Meys will share essential hands-on knowledge and practical R scripting tips. The training is meant as a one-day event. Attendees will get accustomed with a brief history of R, understand main principles of R-language, what Packages are and how to use them to facilitate your day-to-day work. Joris Meys will share his experience on how to find the right answers and resources to complete R challenges. And last but not least, trainees will write their own basic R scripts.  

About the coach

Joris Meys is a co-author of “R for Dummies,” a statistician, R programmer and lecturer at Ghent University. He graduated from the Biology department at the University of Antwerp in 2012. After working as a researcher, writer, and project manager, he obtained a second master's degree, this time in statistical data analysis. He has developed multiple packages and web interfaces for a wide variety of applications. Over the years he has given numerous workshops on R and statistical analysis for both researchers and companies.

Who uses R and why?

R is used as part of the data analysis toolkit in some of the biggest companies in the world, mostly data-driven enterprises: Facebook, Google, Twitter, Monsanto, the FDA, Lloyds, Credit Suisse and AirBnB are among many utilising R on a daily basis.

R has become the primary tool as it provides a flexible, all-in-one, solution for data mining, data analysis, and data visualization. Facebook, which more than two years ago was said to processes more than 500 terabytes of data a day, uses R to understand how its users interact with the service. Exploratory data analysis helps Facebook understand what its users are doing throughout the day and how viral memes propagate through the social network. These companies make good use of R, the Market Research Industry can too. Market researchers need to stay competitive by automating and integrating processes. R combined with the right set of tools, like Nebu Data Hub, provides the solution!

As technology advances, the way data is being used becomes more complex. There are millions of gigabytes of sophisticated data that can help enrich your projects. How to make sense of it and produce actionable insights to clients, that’s the challenge. The most innovative market research projects today don’t consist purely of data collection: It is increasingly about managing and visualizing data.

Innovators enrich their projects with CRM data, transactional data, NPS ratings, brand sentiment analysis, alongside passive data retrieved from online surveys, such as geolocation based on IP addresses, and device used, amongst many others. Those projects are mostly agile, consisting of small iterative steps. Agile market research projects facilitate quicker detection of possible errors, thus providing quicker action and increased efficiency. Survey data is automatically enhanced, integrated and combined with intuitive reporting. Collect, manage, utilize. 

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