Big Data Analytics is the process of examining large data sets, containing a variety of data types, to uncover patterns, correlations, market trends, customer preferences and other useful business information.
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In supply chain, Big Data sits between planning and operations, your operations will give you data which you can then use to plan and optimise with by looking at the insights.
The easy thing to do right now is wonder what the difference between big data and AI is? It's a good question and really, logic dictates that one feeds the other. To make something like AI work, you need lots of data.
So far as I can tell there really isn’t much more to say, yes there is amazing amount of data available now, but quantity is not necessarily quality. Yes, with more data, you can target customers more accurately (i.e. Facebook and Google knowing extremely intricate details so that they can best place ads which appeal to you). But to leverage such a technology across multiple industries efficiently and effectively is still going to take some time. We not only need to capture data, we need to validate its accuracy (making sure it's usable), and build good models to plug the data into in order to finally gain valuable insights from.
In the context of supply chain, every movement of goods is supported by at least one portion of data. For example if you move a pallet from a loading dock to a rack position, a seemingly simple task. You are actually capable of tracking an amazing amount of data from just that movement, think about who picked the pallet up, what machine they were using, when did this happen, how long did it take to travel, which location did they go to, did they confirm the location. All of that comes from one movement.
The good thing is that by investing in these kinds of methodologies and technologies which enable data capture (as well as management for insights) we are progressing what is possible with our data and we are on a daily basis become more intelligent about how we address problems or make future decisions.
Written By Krystian
The good thing is that by investing in these kinds of methodologies and technologies which enable data capture (as well as management for insights) we are progressing what is possible with our data and we are on a daily basis become more intelligent about how we address problems or make future decisions.