As we start to rely more on analytics we are going to start to rely more on artificial intelligence to help us makes sense of the massive amounts of data that we need to examine. This may seem a little "Skynet" like but we are coming to a crossroads with analytics between humans and machines. Radhika Subramanian explores this crossroad in a recent post on Smart Data Collective:
Data analysts are tasked with a search for understanding from increasingly large data sets. Within the field, analysts and data scientists use a variety of tools to extract value and meaning from structured, and more recently even unstructured data. Each new technology represents an incremental improvement in the way that people collect, analyze, visualize, and report our data, making the data discovery process faster and more accessible than ever.
Visualization tools in particular are a critical component as the scale of data continues to grow. The complexity of modern data makes larger data sets incomprehensible, and visualization tools provide an interactive metaphor as users section and explore data. These tools, combined with the ability to look across disparate data sets, give analysts the ability to connect seemingly unrelated data and discover patterns that would previously have taken months of work to uncover or might never have been revealed at all. Humans need these pictures as a bridge between typical rows and columns style text and the enormous data sets that are being created today.
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