A peek into the future?

IBM's take on big data and the world of retailing.

Take-away:
1. Retailers need to filter out noise from data.
2. Predictive analytics strategy 1:

• observing what people are saying on social media outlets and using that to gauge customer sentiment about particular brands
• tweets about a brand , especially from a social influencer needs to be analyzed, and that means going through the connections and reputation he/she has in a a given social network.
• knowing who this social influencer is, and who he/she is saying and then influencing, is getting more and more important over time.

3. Predictive analytics strategy 2:

• requires actually hunting down unconventional sources of data that can offer some rare insight into your specific business.
• IBM has access to real-time performance data from some online retailers, giving it data to conduct performance comparisons in a specific sector of retail business, such as apparel or baby products. 
• Example of usage:
• Performance comparison between the business and its competitors, especially for online businesses 

Questions to be answered:
1. How is Big Data different from the conventional data analysis from queries that we do from our databases?
2. How is it different in terms of implementing this data?
3. What are the sources of big data? How does a business gain the access to different types of data?


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