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Performance measurement and analytics specialist Soasta has announced the release of Data Science Workbench, a query and analysis environment for gaining insight from user experience performance data.
The platform enables users to gain insights, spot trends or identify issues by mining user experience and performance data collected from Soasta and other sources.
“Every system, application, device and end user is streaming petabytes of data every day that can be mined for competitive advantage and strategic innovation,” Brad Johnson, vice president of marketing for Soasta, told eWEEK. “In the future of the digital economy, the winners in every industry will be those who can collect, aggregate, transform and access the key nuggets of information faster than their counterparts.”
Workbench features include a user interface based on the MIT-developed Julia scientific programming language that enables simplified visual exploration of datasets, pre-developed functions and statistical models, plus it includes built-in support and expertise of Soasta’s data science team.
“There is so much data collected, by different sources and in different formats, that really smart folks–like data scientists–have to spend their very expensive time in data manipulatiom,” Johnson explained. “What they really want to do is spend that precious time creating queries to slice and dice data for answers [to] things like what are their users doing that they didn’t know about, how do [users] spend time on their websites before or after they buy something, or how regional users differ in their online researching patterns from users in another geography.”
For example, Johnson said customers can correlate user conversion rates to response time, view most profitable click-paths by region, trend peak user traffic by operating system, or query the data for any other business insights.
Johnson said Soasta’s experience applying big data analytics to an old problem—software performance testing—gives it a unique perspective into mundane tasks that often waste a lot of skilled users’ time digging for results.
Users can now access this information, then slice, dice and analyze the data in a variety of different visual formats.
The platform is available immediately as an annual service package that includes data transformation and access, visual tools and data scientist support.
“It’s important that getting unique answers from data doesn’t become and elite sport for deeply specialized data scientist,” Johnson said. “It’s great to have those folks to handle the hard and hairy issues and to help establish the data frameworks and processes about what data to utilize, and why, but providing a visual, simple and easily accessible means to ask “multidimensional” questions is something that business users, performance engineers, developers and testers should be able to do so that actionable information relevant to their specific needs can be gained without waiting for specialists to free up.”