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Software AG - EN Uhlandstraße 12 64297 Darmstadt, Germany http://www.softwareag.com
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Software AG - EN

Software AG Supercharges Digital Business Platform with High-Performance, Big Data Predictive Analytics

Apama Streaming Analytics Platform seamlessly integrates Zementis ADAPA / All data mining tools' predictive models can be ingested by Apama and ADAPA / Provides all the analytics capabilities a business analyst or data scientist needs

(PresseBox) (Darmstadt, )
Software AG (Frankfurt TecDAX: SOW) today announced the addition of pre-built high-performance, Big Data Predictive Analytics solutions to its Digital Business Platform that make it easier and faster for enterprises across industries like retail, manufacturing, financial services, telecommunications, utilities, and hospitality to expose, anticipate, and act on critical business insights.

Wolfram Jost, chief technology officer, Software AG, said: "The ability to predict what is likely to happen next is essential to satisfying customers, improving operations, and beating the competition. Predictive analytics uses patterns found in historical and real-time data to indicate what is ahead. The addition of predictive analytics enhances the capabilities of our Digital Business Platform and enables enterprises to identify and act on future risks and opportunities in terms of revenue, resources, output and more."

Software AG has embedded Zementis ADAPA (Adaptive Decision and Predictive Analytics) into the Apama Streaming Analytics platform to offer enterprises a comprehensive 'one stop shop' for business insight and analytics. Zementis ADAPA is an extremely fast, standards-based deployment platform and scoring engine for predictive analytics, and uses algorithms that discover patterns in Big Data that might predict similar outcomes in the future.

Unique to Zementis ADAPA is its PMML (Predictive Model Markup Language) deployment and run-time engine. Due to the rich support for this emerging data mining industry standard, predictive models created with all leading commercial and open source data mining tools can be utilized for real-time scoring.

Michael Zeller, chief executive officer, Zementis, noted: "The demand for predictive analytics is exploding. The reality is that businesses employing predictive analytics will be in a better position to support their customers than those without predictive analytics. It's a tremendous competitive edge."

The Digital Business Platform and its newly added predictive analytics capability can support numerous applications, including predictive maintenance, smart metering and manufacturing, supply chain optimization, fraud detection and a number of Internet of Things and 'connected customer' marketing use cases.

Michael Zeller continued: "Too many companies struggle with how to translate their Big Data into actionable insight. By adopting high-performance, Big Data predictive analytics, businesses can leverage a treasure trove of information that enables them to optimize business performance or carve out a differentiating niche in an increasingly competitive landscape through programs such as personalization marketing."

New technologies such as in-memory processing, streaming analytics, cloud computing, Internet of Things and Big Data coupled with faster and cheaper computing platforms and sensors are all contributing to making predictive analytics more easily attainable to help enterprises modernize their analytics capabilities.

Wolfram Jost added: "Software AG has made a strong commitment to help enterprises drive real business value and critical insights across the full spectrum of analytics to give our customers a competitive edge. Our goal is always to put our customers' needs first, and we believe that the Digital Business Platform achieves this. Moreover, we have recently partnered with Mosaic Data Science, who provide advanced analytics and data science support for our customers."

About Zementis

Zementis, Inc. provides software solutions for predictive analytics. The company was founded on the principle that data science teams and IT departments can collaborate seamlessly and efficiently, allowing predictive models to rapidly move from development to deployment, so that businesses and other data-centric organizations can easily incorporate predictive analytics into their routine operations. Agile deployment of predictive solutions is the cornerstone of the Zementis philosophy.

CIO Review recognized Zementis as one of the "Top 20 most promising Big Data companies in 2013", and Gartner named Zementis a "Cool Vendor in Data Science" in 2014. Its ADAPA® and Universal PMML Plug-in (UPPI) scoring engines are designed from the ground up to benefit from open standards and to significantly shorten the time-to-market for predictive analytics in any industry. Customers such as Bosch, FICO, Equifax and Western Union have used Zementis solutions successfully to enhance their predictive analytics capacity and capabilities. For more information, please visit www.zementis.com.

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Software AG - EN

Software AG (Frankfurt TecDAX: SOW) helps organizations achieve their business objectives faster. The company's big data, integration and business process technologies enable customers to drive operational efficiency, modernize their systems and optimize processes for smarter decisions and better service. Building on over 40 years of customer-centric innovation, the company is ranked as a "leader" in fourteen market categories, fueled by core product families Adabas-Natural, ARIS, Alfabet, Apama, Terracotta and webMethods. Software AG has more than 4,600 employees in 70 countries and had revenues of €973 million in 2013. Learn more at www.softwareag.com.

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The publisher indicated in each case (see company info by clicking on image/title or company info in the right-hand column) is solely responsible for the stories above, the event or job offer shown and for the image and audio material displayed. As a rule, the publisher is also the author of the texts and the attached image, audio and information material. The use of information published here is generally free of charge for personal information and editorial processing. Please clarify any copyright issues with the stated publisher before further use. In case of publication, please send a specimen copy to service@pressebox.de.