Lavastorm Analytics Brings Collaboration and Transparency to Analytics

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New Capabilities Provide Non-Technical Users with Insight into How Analytics Were Created

Lavastorm Analytics Engine 6.0 is a new paradigm for analytics that fosters collaboration and transparency throughout the creation and sharing of analytic applications.

The current process for creating and sharing analytic applications is a disjointed chain: authors create analytic programs and share only the resulting data, and none of the underlying business logic, with non-technical business analyst consumers. This broken process provides non-technical consumers with only a static, end-result report that is segregated from the source data used to develop it. Without transparency showing how results were obtained and what data were used, non-technical consumers often lack trust in the results to make key business decisions. Meanwhile, authors, in their attempts to maintain data governance, end up as bottlenecks and barriers, preventing transparency and trust.

With the introduction today of Lavastorm Analytics Engine 6.0, collaboration and transparency are finally delivered to both the authors and non-technical consumers of analytic programs. Lavastorm Analytics Engine 6.0 makes analytics a truly collaborative activity, enabling technical and non-technical users to work together on analysis, anywhere. Additionally, non-technical consumers are now given insight into an analytic program’s underlying business logic, the how and what of the results, improving transparency and trust.

In an increasingly data-driven culture accelerated by demands for Big Data technology and data storytelling, Lavastorm Analytics Engine 6.0 makes life easier for both technical and non-technical analytic users. Authors can now deliver read-only applications showing the business logic of the analytics to non-technical consumers via only a web link with no software installation required. Using that link, non-technical consumers can view data flow logic, inspect interim data, and even re-run an analytic application using dynamic parameter values to serve ad-hoc requests. Lavastorm Analytics Engine 6.0 decentralizes data access without compromising data security.

New Features of Lavastorm Analytics Engine 6.0
●    Authors can now send non-technical analytic consumers a link to an analytic application that is viewable and executable via the web on any desktop or mobile device.
●    Non-technical analytic consumers can now view the “what” and “how” of analytic applications, including data flow logic and interim data, and also execute it using dynamic parameter values.
●    A separate view-only mode is now available for analytic consumers in an HTML5 web interface that requires no installation or download.

Lavastorm Analytics Engine 6.0 Use Cases
There are a variety of scenarios where both authors and non-technical consumers would find Lavastorm Analytics Engine 6.0 to improve collaboration, process, efficiency or even results, including:
●    Quality Assurance managers can send a graph to many people in view-only mode to solicit feedback without requiring all reviewers to download software.
●    Compliance teams can file regulatory compliance reports after easily verifying that all logic and data is correct and consistent with corporate policies.
●    Run-time analysts can execute pre-built analytic applications on-demand with dynamic parameter values to serve ad-hoc requests, while maintaining overall data consistency and accuracy.
●    Analytics can be distributed to an entire organization with business logic intact, showing complete transparency into how they were created and what data was used.
●    Employees can troubleshoot analytics by viewing node properties and status through a web interface without installing or running any software.

Supporting Quotes
“In data-driven cultures, people seek to understand the process and logic behind data management and governance for analytics. Lavastorm is empowering organizations to analyze disparate data types from many different sources. Analytic application producers and consumers can now use tools such as Lavastorm Analytics Engine to gain greater visibility into their data; and identify and surface any issues associated with data quality. With this ability to collaborate across the enterprise via web-based user interfaces, Lavastorm enables organizations to take action in relation to analytical governance in a new way.”
-- John Myers, Managing Research Director for Business Intelligence, Enterprise Management Associates

“Lavastorm Analytics Engine 6.0 is a new paradigm for analytics that fosters collaboration and transparency throughout the creation and sharing of analytic applications. We felt a compelling demand from not only our customers, but also the broader industry, for analytic authors to share their work. Lavastorm Analytics Engine 6.0 provides a data flow user interface that shows the what, where and how that leads to trusted analytic results.”
-- Drew Rockwell, CEO, Lavastorm Analytics

Additional Resources
●    Community and Collaboration: A Big Requirement of the Big Data Landscape by Drew Rockwell
●    Collaboration Comes to Big Data and Analytics by Parag Pathak
●    Introduction to the Lavastorm Analytics Engine Video
●    Twitter - @Lavastorm_News

Lavastorm Analytics Engine 6.0 is available to Lavastorm customers beginning today.

About Lavastorm Analytics
Lavastorm is the agile data management and analytics company trusted by enterprises seeking an analytic advantage. The company’s data discovery platform empowers business professionals and analysts with the fastest, most accurate way to discover and transform insights into business improvements, while providing IT with control over data governance. The company’s solutions have identified business improvements worth billions of dollars for some of the largest corporations in the world. A global company, Lavastorm is headquartered in Boston, MA, with offices throughout EMEA and Asia-Pacific. For more information, please visit

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Kevin York
Kevin York Communications for Lavastorm Analytics
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since: 03/2011
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