Data analytics models still woefully inadequate

One criticism of data analytics models today is that we can miss the important data in between events, says an expert.

While many companies now use data analytics models to predict future customer behavior or real-time data to make business decisions rapidly, SharePoint and business intelligence (BI) expert Scott Robinson says that companies may sometimes be missing key moments to gather analytics data.

According to Robinson, a key overlooked area from which to gather analytics data is the "in-between moments:" moments that might take place between key events that could relay important data.

"We have deliveries, [packages] in transit," Robinson offered as an example. "We can track a package on What about the events that happen between those drop-off points? Places where we're noticing damage that's occurring on a regular basis."

Robinson also noted that ingesting data from devices -- whether they are wearable devices, such as smart watches or Internet of Things devices or otherwise -- can pose issues.

"We have people in the field," Robinson said "whether they are truck drivers, sales reps or homecare nurses -- and they're entering data into devices and trying to interact with information coming back. Entering data on a mobile device isn't a big deal, but the processes we're talking about are complex."

Robinson also talked about the need for greater maturity in data visualization, where our traditional formats haven't caught up with the volume and velocity of the data.

"Data visualization methods have also been problematic," Robinson noted. "The problem we have is that we're dealing with data in new ways and in real time. We tend to render our visualizations of data in old-fashioned ways: We use static graphs. We use graphs that have been ubiquitous for 50 years; we are not up-to-date in relaying the dynamics of data in a way that gets things across. What we lack and what we need is a better visual paradigm for rendering time series information, where I'm watching something change over time."

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