Today at the Strata Conference in Santa Clara, cloud analytics specialist SiSense unveiled a new version of its flagship offering that has been optimized for smartphones and tablets. With the number of mobile devices set to exceed the world’s population this year, the update is a natural (and arguably overdue) evolution for a startup seeking to make data insights more accessible to end-users.
Accessible data is a central theme for many of the Big Data companies with product releases this week, and SiSense is no exception. Mobile is key to making data more accessible to end users, but anticipating a bevy of varied access points through browser applications and devices doesn’t come without its challenges.
Overcoming barriers to deliver real-time analytics on mobile
“When it comes to business analytics on mobile, the biggest challenge is technical,” said SiSense CEO Amit Bendov. “Suppose you have a data set of five billion records and you are an executive who wants to access and query sales numbers from your mobile device, how do you get results in close to real time? And how do you ensure you can scale to massive amounts of users and queries? That’s a technical challenge.
“Overcoming these barriers meant marrying the front-end design with a powerful back-end that could support queries on terabytes of data. All the technological innovations we introduced over the past 12 months were leading up to this,” he went on.
As WinWire CEO Ashu Goel explained at last year’s Appcelerator Enterprise Platform Launch meetup, the rapid consumerization of IT is driving a convergence of Big Data and mobile in large and historically slow-moving organizations.
“In the traditional enterprise we used to build a lot of large, monolithic applications to solve problems. That world is completely changed now,” the executive told SiliconAngle correspondent Jeff Frick. “If you really take a look at your phone, on average you’ve got 70 to 80 different micro-apps. You don’t go to www.weather.com, you just go to your weather app and you have immediate information available today. That’s what going on in the enterprise too: people who are on the move are looking for these applications that deliver information to them…when they need it.”
Mobile access was so important to SiSense’s update that the company completely rethought its application design. Here’s why:
“The visualizations were reworked from scratch to support responsive design — and getting the solution run optimally on any device involves more than scaling, it’s designing the front-end to optimize it for each respective mobile device and desktop,” explained Bendov.
Mobile delivery requires backend optimization
Currently showcasing at Strata, SiSense 5 features push notifications and the ability to drill down into specific metrics for a more detailed view of the underlying patterns. It also enables users to integrate information from multiple sources and incorporate the resulting datasets into custom dashboards that can be shared via email. On the backend, the service is powered by a homegrown technology called “In-Chip Analytics,” which snagged the Audience Award at last year’s Strata Conference after processing 10 terabytes of data on a $10,000 Dell system in a record time of 10 seconds.
“Our unique In-Chip technology allows users to analyze 100x more data at 10x the speed of traditional in-memory solutions,” said Bendov. “And while performance of traditional solutions degrades with increased load, our Crowd Accelerated BI technology nets faster and smarter query results as users increase. Costly bottlenecks are avoided and users benefit from each other’s queries even when queries are not identical. Old school BI nets users.”
contributors: Maria Deutscher
photo credit: Dell’s Official Flickr Page via photopin cc
Kristen Nicole has also contributed to other publications, from TIME Techland to Forbes. Her work has been syndicated across a number of media outlets, including The New York Times, and MSNBC.
Kristen Nicole published her first book, The Twitter Survival Guide, and is currently completing her second book on predictive analytics.