Analytics Systems

Zoomdata Raises $17M to Beautify Big Data

The big data analytics space continues to be a hotbed of investment and activity as startup Zoomdata announced Monday it has raised $17 million to help it achieve its goal of analyzing data faster than its competitors and presenting it more attractively than them too.

The two-year-old company closed $17 million in series B funding led by Accel Partners , bringing its total raised to date to $22 million. Founder and CEO Justin Langseth said it will use the fresh cash to double down on engineering -- the majority of its 50 employees are engineers today -- and expand its sales and marketing teams.

Zoomdata is hoping to benefit from the same "late-mover advantage" that helped Google (Nasdaq: GOOG) become the leading search engine despite the existence of dozens of other choices. It built its patented micro-query software and stream-processing engine from a mobile-first perspective that Langseth says can analyze data in seconds. The company connects to legacy storage databases as well as Hadoop, NoSQL and Spark to present all the data in a unified and -- Langseth claims -- "beautiful" interface.

"We are focused on design; making it beautiful and super easy," he says.

Beauty's in the Eye of the Data Scientist
Zoomdata pulls in data from traditional storage databases, Hadoop, NoSQL and Spark and shows it off on one, easy to digest dashboard.
Zoomdata pulls in data from traditional storage databases, Hadoop, NoSQL and Spark and shows it off on one, easy to digest dashboard.

The CEO equates Zoomdata's micro-query architecture to a video that gets increasingly crisper as it loads. Data sharpening technology provides a sketch of the data that continuously updates through stream processing until the full picture is clear.

Zoomdata primarily serves the enterprise space with 20 customers including Deloitte, GoPro and Juniper Networks Inc. (NYSE: JNPR), but it is also in trials with telecom and cable operators. Langseth says it's working with a satellite company to collect data from set-top boxes, including when and where consumers stop, fast forward and rewind content to build better targeted ads.

It is also working with a big network equipment company -- not Cisco Systems Inc. (Nasdaq: CSCO) -- to understand internal support and maintenance issues on devices such as firewalls and routers, but it also provides that same dashboard to the end customers who are paying to own the devices. It collects performance and demographic data in the cloud, network or on the device itself, and offers its service branded or white labeled.

Want to know more about big data? Check out our dedicated analytics content channel here on Light Reading.

"It's entirely software, but not a cloud service," Langseth says. "We don't require telcos send all the raw data to us. We're believers that data analysis software should run as close to data as possible."

The startup is playing in a hot space, made more important by the fact that operators are connecting millions of new sensors to their networks. The Internet of Things is generating massive amounts of data, oftentimes that requires real-time action -- that's a notion that enterprises and operators are still trying to get their heads around. (See Cisco Paints IoT Into the Big Data Picture.)

Langseth says what differentiates Zoomdata from established vendors and startups such as Tableau, Guavus Inc. and others is the speed of its analysis that combines continuous event processing and historical analytics through a "data DVR," and the simplicity of its platform, which also works on mobile devices. (See Guavus Colors in Its Big Data Picture and Big Data Attracts Big Dollars, New Faces.)

"We started the company two years ago focused on Hadoop," Langseth says. "Everyone else has built up older architecture based on relational databases. Because we got started late, we have that last-mover advantage," he believes.

— Sarah Reedy, Senior Editor, Light Reading

SachinEE 10/20/2014 | 12:44:38 PM
Re: data dashboards What if you could convert data in such a way that even if you didn't need it, you could probably sell it to data mining companies? For example in big data sets, there are many entry points for data which may be important or unimportant, and the companies that use such data mine them and what's left they convert it into a data that can be used by multiple scavengers.
SachinEE 10/20/2014 | 12:39:04 PM
Re: data dashboards I think companies should first conduct a wide area research on consumers in finding out what kind of needs the company needs to fulfill in order to ensure proper support of confidence from the consumers. It is true though that people may or may not have their way (because companies will take the route that is more profitable to them) but even then companies should place consumers above their profits.
Ariella 10/7/2014 | 10:27:40 AM
Re: data dashboards @mhhf1ve I agree that it could be done and probably should be done. It's just a matter of getting people to come to an agreement that doesn't assure their favored approach will become the universal one. That's what could take some time to work out. 
mhhf1ve 10/6/2014 | 10:22:09 PM
Re: data dashboards Ariella, Yes, that's the main problem with some huge datasets -- the raw sources come from multiple origins that didn't necessarily plan ahead of time to have their data aggregated with other sources. So then you have a mess of data that needs to be tediously cleaned up before it can be made useful. There have been some attempts to do automated cleaning of location data (so that zip codes or city names can be automatically turned into GPS coordinates or vice versa), but generalized data clean up would be a huge artificial intelligence win... if it could be done. (And maybe something like IBM's Watson could do it?)
Ariella 10/6/2014 | 7:46:45 PM
Re: data dashboards @mhhf1ve but wouldn't the real trick be getting everyone-- even those using other visualization services -- to abide by the same formats? That is not likely to happen for some time?
mhhf1ve 10/6/2014 | 7:04:50 PM
Re: data dashboards hmm. does Zoomdata also help "clean up" data and try to get it into standardized formats? I think that's often the biggest hurdle for data analysis projects -- the data you have is messy and needs to have duplicate data points removed and all kinds of other bad data points taken out.... I was disappointed when Twitter acquired DabbleDB and that service died ... because it had, in addition to some cool data visualization tools, a few nice data import and clean up functions that helped to organized data into commonly useful forms.
sarahthomas1011 10/6/2014 | 9:27:03 AM
data dashboards Zoomdata' emphasis on simple, pretty dashboards is really important too. I think a lot of companies get overwhelmed with data not just because of the sheer volume of it, but also because they don't understand it no matter how distilled down. It needs to be readable by everyone from engineers to sales folks, at least a high level.
Sign In