‘Data activation’ unleashes trapped and siloed data, says WANdisco
It’s already an enormous challenge for businesses to merely collect the data from large Internet of Things (IoT) deployments. Using it is another problem entirely. The distributed computing experts at WANdisco think they have the right solution with Edge to Cloud, an IoT data activation system they announced the launch of this week.
Edge to Cloud leverages cloud-resident artificial intelligence (AI), machine learning (ML) and data analytics, promising to help make IoT datasets usable in any cloud environment, if you buy the company line. WANdisco says Edge to Cloud automates IoT and file data processing across edge systems. It can handle any data set size, according to the company, which touts petabytes (Pb) of data moving through the service daily, more than an exabyte (one billion gigabytes) per year.
WANdisco touts Edge to Cloud’s instant deployability, flexibility over sources, targets, and data sets, and advanced controls to help manage network bandwidth and path mapping.
Edge to Cloud is an outgrowth of WANdisco’s Data Activation Platform, said the company. Data Activation Platform was developed to help businesses manage the movement of data and metadata stored using Apache’s Hadoop open-source framework.
WANdisco is pushing “data activation” as the catchphrase du jour. Tony Velcich, who heads product marketing for WANdisco, explained in a recent blog post.
“Data activation requires the combination of data collection, filtering, aggregation, and storage at the edge (IoT), and then moving that data to the cloud, where it can be stored inexpensively and durably, processed at any scale, and accessed from the wealth of innovative ML and AI services that are available in the cloud,” he wrote.
IoT data sets present some unique challenges, Velcich said. They include data production faster than companies can handle, data that’s distributed too broadly, and poor cloud integration. Edge environments have no single central data aggregation point, and large-scale data generation needs filtering and aggregation at the edge. Data is stored in staging locations, and can be accumulated continuously or in batches, he explained.
“This type of data landscape can make it challenging for chief data officers and other data leaders to wrangle and activate their company’s valuable data for business impact,” he said.
Edge to Cloud incorporates a graphical user interface, command line tools and a REST API. It supports Amazon Web Service (AWS), Microsoft Azure, Google Cloud Platform (GCP) and other cloud providers, as well.
