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Big Data: How to Target Your Learning Community

By on December 15, 2016

In the marketplace we work in today, organizations need to stay competitive. In order to do so, quite frankly, you need to know what’s going on around you. As such, some companies have begun to do more with their data than ever before. The spread of data analytics and the joys of user research is exciting in itself, if like me, you are a fan of understanding exactly why people do things in certain ways.


What is big data?

The paradigm and power of data has evolved into a phenomenon known today as “big data” – very large data sets that are analyzed for key patterns and trends to ultimately explain unstructured data in a variety of complex environments. Recent trends have shown that an increasing number of organizations are adopting and investing in the power of big data.

So, why is big data important?

When done correctly, understanding big data allows companies to gain a better understanding of their organization, clients, products, services – and their competition. Ultimately, this information is useful because it allows for improvements otherwise not possible [click to tweet], such as inefficiency reduction and improvement in customer satisfaction, costing model structure, resourcing, and service offerings.

In the learning community, the Tin Can API or xAPI is among the most popular learning technologies with regards to big data. In a nutshell, this technology was created to be simple, intuitive, and adaptive for m-learning, e-learning, simulations, virtual reality, and even collaborative learning. This means more precise data points and targeted information to help your organization.

Ethical implications of learner performance data in training

In a white paper published by the CAE, Ethical Considerations for the Use of Big Data in Training Organizations, 20 major ethical considerations are discussed. These considerations range from maintaining transparency to ensuring organizations and stakeholders take ownership of, not only collecting and properly depicting accurate datasets, but also utilizing a proper analysis process. The comprehensive list offers a snapshot of key implications for big data.  In addition, ethics and big data in the training domain are considered, as well as some specific legal implications and privacy considerations.

Using big data: tips for success

  1. Maintain transparency – Maintain an equal level of transparency between data controllers, collectors and test subjects.
  2. Laws – Be aware of the laws that govern your specific area of operation, business, audience, and ability to apply data findings.
  3. Practical usage – Understanding how to collect big data is only step one. The bigger challenge is how to effectively assess your data sets. Once you figure this out and apply it to your specific user case, you’ll be on your way.
  4. Stay up to date – Big data is evolving more and more each year. By implementing an ear-to-the-ground approach, you can keep up with the times and be on top of tips and emerging tools in the community.

How are you using big data in your organization? 

By Christopher Gunn

Christopher GunnChris Gunn is Learnography’s Solutions Consultant, focusing on new business development. With a bachelor’s degree in Political Science and Economics and a Master’s in Public Policy, he enjoys the thrill of combining theory and natural progressions in the economy with innovative thinking and learning principles. He is passionate about finding new ways for people to learn and is a longstanding advocate of information sharing and collaboration. In his spare time, Chris is into deadlifts, Nike sneakers, music festivals and basketball.