Chris Raphael

Where to perform analytics often depends on the business need and device capabilities. Dell and TDWI describe IoT architectures and use cases for edge analytics.

There’s a growing need to analyze fast data at the network’s edge. Use cases and approaches from a variety of IoT companies are discussed.

With the acquisition of The Weather Company’s digital properties and a Twitter data collaboration, IBM can offer a range of more advanced data products and services.

Cisco has made no secret that its intent to acquire ParStream is a play in edge analytics.

Big Data trends and emerging technologies include self-service data preparation, the cloud, Internet of Things, data-as-a-service, and embedded analytics.

Mobile marketing needs to do a better job of catching customers in the moment. Better integration between search, maps, and real-time store data (is the item in stock?) presents a new frontier, as do developments such as digital coupons.

With growing use of “near-me” searches, business must win over customers in “micro-moments.”

To make better decisions using data requires operational analytics. That can include embedding analytics on different systems and using disparate data,

As smart grid projects take off, especially on the distribution network, utilities must make the case for real-time analytics.

GE’s “digital power plant” employs sensors and real-time analytics across the entire power-production ecosystem, enabling uses such as the optimization of electricity production and predictive maintenance.

Real-time marketing can entail everything from triggered emails to social media monitoring and digital coupons. Marketers say they lack the ability to search user-generated content in real time, which opens opportunities for software vendors.

Putting the customer first often means using real-time analytics, especially in areas such as data intelligence and customer research.