July 19, 2017
I had a delightful time at Big Data Toronto. This is the second year that I have attended, and it has once again been full of useful information, so I thought I’d give you a rundown of the three highlights for me. If you want to read more about Big Data Toronto, check out Jessica Shields and Edmond Chan's posts.
Analytics impacts everyone
I glanced down at the name tags of numerous attendees and found that there was a wide variety of people from different industries and departments. From Marketing Managers and Senior Vice Presidents of Sales to Strategy Analysts and Data Scientists, it seemed like every department – and every level – was present. This shows how broad the implications of analytics are; it matters to everyone. So, no matter who you are or what your role is, you will find that data permeates everything that you do, and as a result, you need to consider predictive analytics as part of your plan forward.
Security is vital as we become more data-heavy
I noticed that there were several vendors that were focused solely on securing data both at rest and during transfer. This is a concern that all organizations face as we enter Industry 4.0. Torrents of data are flowing to the cloud, and it all needs to be protected. Not only is this an essential part of our analytics project, but privacy is also important for us. As we move forward, we will be deliberate in ensuring that both security and privacy are preserved.
Mining value from unstructured data is the next frontier
Sentiment Analysis is not a new term. However, it seems that we have yet to hone in on the best recipe for succeeding at turning unstructured data, like comments and notes, into something meaningful that can be used by predictive models. Thomson-Reuters is still working on this. Facebook is too. Meanwhile, some organizations use Amazon’s Mechanical Turk which simply means using a human expert to hand-categorize the data.
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