big data and thick data
The speaker in this video is sharing information concerning big data and also thick data. People need to make accurate decisions, and this is the main reason why they are careful when interacting with big data. Many organizations used big data to discover some patterns which will help them come up with new strategies (Dumbill, 2013). Organizations should not ignore any data even if it comes from a minor researcher. The data may be useful in some way, and they may have lost an opportunity. The speaker gives an example of how Nokia ignored the data she had collected from different interactions in China.
Nokia didn’t see the need for her data since they had big data at their disposal. After ignoring the data, the company ended up losing more customers, and it didn’t succeed as expected. The speaker explains the need for correctly analyzing big data to draw insights. She says that there is no higher risk than being blind to the unknown. She also explains that big data systems need people, such as ethnographers and user researchers. These people will help in collecting thick data.
According to the speaker, thick data is precious data from humans that cannot be quantified. Organizations should integrate big data and thick data so that they can form a complete picture (Alles & Vasarhelyi, 2014). Big data offers insights, while thick data makes the big data useful. When an organization integrates the use of both big data and thick data, it will be able to work with data that is not yet collected. For instance, the organization will ask a question like why, how, and this will help in understanding the data better. All organizations should consider making use of both big data and thick data.
References
Alles, M., & Vasarhelyi, M. (2014). Thick data: adding context to big data to enhance audibility. International Journal Of Auditing Technology, 2(2), 95. doi: 10.1504/ijaudit.2014.066237
Dumbill, E. (2013). Making Sense of Big Data. Big Data, 1(1), 1-2. doi: 10.1089/big.2012.1503