Big Data has emerged as a source of competitive advantage in the enterprise, but many organizations are still struggling to harness the power of analytics due to the complexity and overhead associated with transforming statistics into actionable business insights.

And fast-growing startup called Platfora is working to tear down these barriers with a Hadoop-based BI solution that aims to make information more consumable for decision makers while “enabling new kinds of Big Data Analytics previously only relegated to the realm of data scientists and engineering teams.” According to founding CEO Ben Werther, his firm is making the framework more accessible through a combination of self-service analysis capabilities and interactive visualizations.

“What we have done is build a Big Data Analytics Platform that is native to Hadoop and delivers the facts at the speed that the business demands. We invested heavily to process big data in memory and eradicate the need for any business to have to suffer long waiting times from legacy analysis,” Werther wrote in a blog post highlighting the debut of Platfora Big Data Analytics Platform 3.0, the latest version of his company’s flagship offering.

What’s New

The new release introduces several major enhancements, most notably an event stream analysis tool that the company hails as an industry-first. Business users can leverage the function to correlate event-driven data such as contact center records with raw HDFS data to better contextualize metrics.  Platfora is sectioning off data analytics into familiar and realistic “services” in order to broaden its access and usability for a broader range of employees, empowering them to make better decisions based on facts instead of “gut instinct.”

“Simply put, Big Data analytics from companies like Platfora provides users with better access to facts,” Werther tells us. “When you have the all the facts the gut instincts that you make are better informed and will lead to a better decision making outcome. You can’t rely on making decisions on feelings alone.”

Also new to the platform is an object-based “data catalog” that structures information around customers, products and others points of interest. This feature is joined by a segmentation tool for identifying common patterns across multiple data sets, and a set of new collaboration and integration capabilities.

Disrupting the Big Data Market

Platfora is quickly making its way up the Big Data foodchain. Established in 2011, the first raised over $27 million in funding to date and lists high-profile companies such as Citigroup and Netflix among its customers.  And their efforts haven’t gone unnoticed.  Wikibon Principal Analyst Jeff Kelly named Platfora as a disruptor in the Big Data economy, furthering initiatives to make analytics accessible to more end users within an enterprise organization.

Read More : 4 of the most disruptive startups in BI

Kelly notes the innovation driving Platfora and others in the market to deliver improved integration for BI solutions, but also recognizes the risks still plaguing these disruptors.  It’s these challenges Platfora is addressing with today’s release.

“The good news for business users is that there are a number of relatively new vendors on the market that, unencumbered by legacy architectures and products, are providing just such capabilities. These include Tableau Software, QlikTech as well as Hadoop-focused vendors like Platfora and Datameer,” says Kelly.

“But it’s very early days for these vendors, and the potential for this market to itself stall exists. The risks include risk-averse IT departments preventing business users from adopting these self-service business intelligence applications and instead clinging to BI shelfware from legacy vendors, as well as the potential for new vendors themselves to lose focus and add bloatware to their products to placate IT.”

Tackling the Integration Challenge

For Platfora, such integration challenges are very real, and today’s update reflects the growing need for its platform to make data more digestible and better able to cross-reference for improved integration.  According to Werther, agility and a strong understanding of what end users need help Platfora tackle the ongoing issues regarding data democracy in the enterprise.

“A key requirement is that the integration of diverse datasets needs to be agile, iterative and may have different characteristics, depending on the type of analysis being done (e.g. data discovery, event analytics, predictive). Hadoop is the perfect data reservoir for the raw material — i.e. organizations can feed datasets there without needing to bake in an integration a priori,” Werther explains.

“Then Platfora Big Data Analytics provides a visual data catalog and that allows users to connect these diverse datasets at a metadata level, and our deep processing (i.e. automatic map-reduce jobs pushed down to Hadoop) can perform transformations, aggregations and correlation automatically based on the questions that the user wants to answer.”