Essential Guide

IoT analytics guide: Understanding Internet of Things data

A comprehensive collection of articles, videos and more, hand-picked by our editors
Evaluate Weigh the pros and cons of technologies, products and projects you are considering.

Mobile apps, machine data shape analytics trends in 2014

In 2014, organizations looked to new trends and technologies to get on the upside of the torrent of data flowing into their systems -- capturing and analyzing machine data generated by sensors, eyeing new data management platforms in search of more processing power, and increasingly moving to put mobile data in the hands of business users. In addition, more and more companies turned to social media to better engage customers and to try to influence their buying habits.

This special, year-end episode of BizApps Today assesses some of the top 2014 technology trends in business applications, data management and business intelligence. TechTarget editors Lauren Horwitz, Ed Burns and Craig Stedman discuss developments that are enabling successful data analytics and customer engagement initiatives -- and what's slowing down adoption in some cases.

First, Horwitz, executive editor of SearchContentManagement and SearchCRM, explains to host Joe Hebert how developments in the past year have further placed power in the hands of consumers. In the so-called age of the customer, she says, Internet and mobile technologies have given customers the freedom to say, "We want to talk to you when we're ready to -- on a mobile device." So companies increasingly have turned to social media platforms to communicate with and market themselves to customers, branching out on social networks like Facebook, Twitter and LinkedIn. "But the danger is they feel this need to be on all of these channels without really doing it in a meaningful way," Horwitz says.

Organizations need to focus on social platforms that work with their constituencies and their products, according to Horwitz. Companies like Uber and Sidecar, she says, have proven that "there are new business models … [that] enable customers to be far more involved in the building of the brand."

Horwitz also touches on mobile data, which she sees as priority No. 1 for many organizations. Mobile customer relationship management applications have given salespeople "an arsenal of powerful data," she says, while mobile analytics allows business executives to "make business decisions that they weren't able to previously."

Next, Burns, site and news editor for SearchBusinessAnalytics, discusses the hype that developed this year surrounding the network of data-collecting machines -- popularly known as the Internet of Things -- and why it might be too early for some companies to benefit from the IoT. But, he says, there is legitimate business value to be had for organizations whose operations are reliant on industrial equipment and other machinery -- "like shipping, manufacturing and public utilities."

SearchDataManagement executive editor Stedman revisits a topic discussed in a past episode of BizApps Today: the Hadoop data lake. The release of Hadoop 2 in late 2013 and the increasing availability of SQL-on-Hadoop tools have made it "easier for organizations to analyze data in Hadoop" and run a variety of applications on top of the distributed processing platform, he says.

Still, the data lake remains an emerging concept, Stedman adds. And vendors of relational databases have made moves to hold back its expansion into the territory of traditional data warehouses. For example, he says, the addition of in-memory processing capabilities to mainstream relational databases allows for "large volumes of structured data that otherwise might get tossed into the data lake on a Hadoop cluster."

Where will organizations take their data management, CRM and analytics initiatives in 2015? Tune in to the next episode of BizApps Today to find out.

Text by Joe Hebert, associate managing editor for e-publications. Email him at jhebert@techtarget.com and follow him on Twitter: @jhbrt_TT.

View All Videos

Essential Guide

IoT analytics guide: Understanding Internet of Things data

Join the conversation

1 comment

Send me notifications when other members comment.

By submitting you agree to receive email from TechTarget and its partners. If you reside outside of the United States, you consent to having your personal data transferred to and processed in the United States. Privacy

Please create a username to comment.

Work performed within our IoT would be used widely with the aim to generate high quality results, prototypes with impact on the entire society.
Cancel

-ADS BY GOOGLE

SearchBusinessAnalytics

SearchAWS

SearchContentManagement

SearchOracle

SearchSAP

SearchSQLServer

Close