It’s a week of Big Data celebration with #BigDataSV kicking off today, and the Strata Conference taking place right across the street. As expected, a number of product announcements have hit the news stream this week, as Big Data players like Cloudera, Red Hat and MapR release updates and fresh services that all seem to strive for one thing – making data, and databases, easier for end users to access.

Cloud and mobile both play huge roles in the proliferation of Big Data solutions for the real world, and predictive analytics provider Alpine Labs is also helping business users make the most out of their information with a purpose-built collaboration solution called Chorus. On display at Strata, the web-based tool enables teams to work in tandem via a drag-and-drop data visualization component described as being “almost as easy as using Facebook.”

“Alpine Chorus is a server-based solution that not only acts as the one-place for managing data access and models but it is also the central place for managing users,” said Steven Hillion,  Chief Product Officer at Alpine Data Labs. “We do not actually store datasources on Chorus.  In fact, we use a technology called “In-Cluster Analytics” which allows us to work with data, wherever it is stored – without ever having to move it around.”

Keeping data svelt

The software doubles as an application layer for running algorithms directly on Hadoop without having to move data back and forth from third party tools. Built-in search functionality rounds out the package, providing self-service access to different types of information that would not otherwise be immediately available.

Hillion also noted that “with this new product, we are giving all ‘Data People’ the tools and processes they need to build a ‘Data Nation’ around them. This means engaging all relevant people in the process of Data Science — from executives to business analysts to data engineers, to partners.”

But making data management as easy as using Facebook still comes with its challenges, particularly when you’re talking about distributed access to end users through browser-based applications.

“It’s the trade-off between making things fast and simple versus something that’s accurate and comprehensive,” Hillion explained. “On the one hand you want to interact with the data without any lag or long-running calculations, but on the other hand it can be time-consuming to crunch through all of the data to get the complete picture. It’s not impossible to deliver the full solution, with caching, sampling and statistics, but it’s a lot of work.”

Does real-time data play a role in the Data Nation?

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As real-time data becomes a goal for more organizations and service providers alike, I asked Hillion what role real-time analytics plays in mobilizing this “Data Nation.”

“It depends on the organization,” he replied. “Obviously financial firms are often pretty interested in rapidly updating and applying models in order to do high-frequency trading, whereas real-time analytics may be less interesting in education, for example. For most organizations out there, the first step (beyond BI) is really to do any sort of advanced analytics on their growing datasets, and that presents challenges enough in terms of data gathering, data science resources, automation, and so on. Often real-time analytics is further out in the roadmap.”

Hillion has graced us with his presence before, stopping by theCUBE during our last blow out event, #BigDataNYC. See his entire segment below.

photo credit: bluefountainmedia via photopin cc