IoT Analytics, Dell Statistica, and Taking Time Out at Sanofi

Statistica 13.1 Network Analytics

Dell Statistica 13.1 features new network analytics capabilities that enable users to combine the power of predictive analytics with human expertise to better detect fraud and understand relationships within complex networks.

Advanced analytics platforms, Gartner says, not only make experienced data scientists more productive, but are increasingly targeted at “citizen data scientists.” Providing these “power users” (whose primary job function is outside of the field of analytics) with a visual workflow environment for leveraging predictive analytics, considerably expands the segment of the analytics market—advanced analytics—that Gartner predicts will attract 40% of enterprises’ net new investment in business intelligence and analytics by 2020.

In its most recent Magic Quadrant for Advanced Analytics Platforms, Gartner has moved Dell into the Leaders quadrant, joining SAS, IBM, KNIME, and RapidMiner. Two years after acquiring StatSoft, Dell “has executed on an ambitious roadmap,” says Gartner. The latest milestone in this roadmap was announced on April 14, 2016, when Dell introduced a new release of the product, Statistica 13.1. New features address ease of use for citizen data scientists, heterogeneous data environments, and the rapidly growing IoT analytics requirements.

At the launch event, Tim Alosi, Director of Data Analytics at Sanofi, talked about the past and future of IoT analytics, saying “We’ve been doing IoT for 20 years, we just never called it IoT.” Alosi heads a dedicated process analytics team within Sanofi’s IT organization, overseeing 112 plants worldwide. While manufacturing processes have always involved sensors monitoring in real-time environmental and other conditions, recently the 70,000 sensors in 3 of Sanofi’s plants have been centrally linked. This allows the analytics team to evaluate 100 million data points per day.

“Real time data is really messy,” says Alosi, highlighting the key challenge of IoT analytics – unlike other analytics data, the IoT data is not evenly spaced. Overcoming the challenges, however, will improve drug safety and change the company’s scope of operations. “IoT will allow us to watch that drug as it leaves our plant, travel between distribution centers, and then gets to the doctor’s office,” says Alosi. “IoT will allow us to monitor the product as far as possible to ensure it’s still safe as we expected,” he adds.

The larger benefit of data collection and analysis is the “compression of time,” between when the data is available and when it is possible to act on it, between the determination of a required process change and its execution. Faster and faster is how the world goes for Sanofi and any other large and small companies today. IoT analytics opens new venues for finding in real-time the time that can be taken out. “’Industry 4.0’ technologies – digitization, collaboration, and IoT will help us reduce the time it takes to react,” says Alosi, using the latest buzzword to describe his current reality.

“Given the young age and high complexity of the IoT data environment, it’s not surprising that the ‘analytics of things’ isn’t very mature yet,” says analytics guru Tom Davenport. Dell responded to this challenge with this new release of Statistica by providing “edge scoring” capability which enables organizations to address nearly any IoT analytics use case by running analytic workflows directly at the edge of the network where data is created, allowing for “immediate action to be taken at the point of impact in response to data insights.”

Statistica is a “Dell-scale global analytics franchise,” according to general manager John Thompson. Given Dell’s ambitions to become a much larger enterprise IT provider, it remains to be seen what role analytics will play in its future. There is no doubt, however, that IoT analytics will turn into the next battle ground for advanced analytics.

Originally published on