Infogix Introduces Data Science as a Service

    NAPERVILLE, IL, April 08, 2016 /24-7PressRelease/ -- Infogix, a leader in helping companies provide end-to-end data analysis across the enterprise, today unveiled Data Science as a Service, a change agent to augment in-house analytics teams/efforts quickly with a cost-effective and experienced advanced analytics capability. The objective is to facilitate convenient scaling up or down to peaks and valleys of advanced analytics project requirements, and help accelerate go-to-market and ROI.

Forrester Research estimates most companies analyze a mere 12 percent of their data. The challenge isn't that organizations don't have the right analytics teams in place; rather they are constrained on resources, with the demand for the application of advanced analytics in multiple areas of the business far out-weighing the supply of qualified skill sets. Yet the competitive advantage of collecting and effectively analyzing the ever-increasing amounts and types of data is clear. In a new report by IDC, they estimate that by 2020, organizations able to analyze all relevant data and deliver actionable information will achieve an extra $430 billion in productivity benefits over their less analytically oriented peers.

As organizations struggle with the challenge of the evolving big data environment and being able to scale to address several advanced analytics efforts in parallel, Infogix has introduced Data Science as a Service, a convenient and cost-effective approach that leverages a considerably experienced data science group to complement or extend in-house analytics teams and fill needs on a short-term or long-term basis.

"Infogix goes beyond offering organizations a team of highly qualified data scientists," said Paul Skordilis, executive vice president at Infogix. "We provide customers with the right combination of business domain knowledge, extensive experience in big data and advanced analytics technology, software expertise and on-site versus off-site presence, with a direct focus on ensuring quantifiable value. Infogix understands that, in addition to the ability to successfully apply advanced analytics to business problems, the skill set should include the experience to operationalize those models in a way that is well integrated with existing, proven work flows and processes."

As an extension of the customer team, Infogix assembles the optimum, self-sufficient data science team to accomplish a part of the project or an entire project based on the scope and required outcomes of the engagement. The customer retains the deliverables at the conclusion of the engagement.

"By providing a wide array of advanced analytics experience from all stages of the customer lifecycle, Infogix is able to help organizations turn business problems into opportunities in a cost-effective manner," said Skordilis. "Infogix works with customers to address a number of application areas such as fraud/risk analytics, customer analytics and operations analytics with the end goal of providing quantifiable outcomes that give our customer's the competitive advantages they seek."

To discover more about Infogix's Data Science as a Service results, visit http://www.infogix.com/data-science-as-a-service/.

About Infogix, Inc.
Infogix helps solve business challenges by analyzing data as it moves through complex business environments to improve the customer experience, corporate profitability and operational efficiency. The Infogix Enterprise Data Analysis Platform improves data quality, ensures effective transaction monitoring, provides balancing and reconciliation, identifies and predicts fraud and customer behavior. Infogix provides best-in-class solutions that seamlessly integrate into operations and allow clients to manage highly complex, data intensive business environments. By analyzing, processing and monitoring 100 percent of data in real-time or in batch, Infogix is able to provide proactive and actionable intelligence to manage operational workflows and steps. To learn more visit http://www.infogix.com or @Infogix.

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