advanced analytics

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Published By: Secureworks ABM UK 2017     Published Date: Oct 23, 2017
SecureWorks provides an early warning system for evolving cyber threats, enabling organisations to prevent, detect, rapidly respond to and predict cyber attacks. Combining unparalleled visibility into the global threat landscape and powered by the Counter Threat Platform — our advanced data analytics and insights engine —SecureWorks minimises risk and delivers actionable, intelligence driven security solutions for clients around the world.
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cyber security, cyber security framework, data security, firewall, general data protection regulation, incident and problem management, information security, intrusion detection
    
Secureworks ABM UK 2017
Published By: Fiserv     Published Date: Nov 09, 2017
Financial institutions seeking to attract new customers and revenue channels are expanding into digital services, real-time payments and global transactions. However, with every new service, criminals are developing innovative ways to infiltrate financial systems, and older technologies that mitigate fraud no longer work as effectively. So how can financial institutions respond to this growing threat? Fortunately, more advanced technologies hold great potential for real-time financial crime mitigation. Learn about five current and emerging technologies that could impact money laundering and fraud mitigation, including artificial intelligence/machine learning, blockchain, biometrics, predictive analytics (hybrid model) and APIs. Read the latest Fiserv white paper: Five Tech Trends That Can Transform How Financial Institutions Detect and Prevent Financial Crime.
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kyc, know your customer, beneficial ownership, financial crime, financial crimes, compliance, enhanced due diligence, suspicious activity report
    
Fiserv
Published By: SAS     Published Date: Aug 03, 2016
Tax fraud is already prevalent, and fraudsters are more sophisticated and automated than ever. To get ahead of the game in detecting fraud and protecting revenue, tax agencies need to leverage more advanced and predictive analytics. Legacy processes, systems, and attitudes need not stand in the way. To explore the challenges, opportunities, and value of tax fraud analytics, IIA spoke with Deborah Pianko, a Government Fraud Solutions Architect within the SAS Security Intelligence practice.
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finance, tax fraud, security, protecting revenue, opportunities, analytics
    
SAS
Published By: SAS     Published Date: Apr 25, 2017
Insurers have long been plagued by fraud, error, waste, and abuse in health care payments. The costs are huge – amounting to as much as 25 percent of payments made. Today’s data management and analytics platforms promise breakthroughs by incorporating comparative and behavioral data to predict as well as detect loss in all its forms. To explore the opportunities and how insurers can capitalize on them, IIA spoke with Ben Wright, Sr. Solutions Architect in SAS’s Security Intelligence Global Practice.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Quality 4.0 isn't really a story about technology. It's about how that technology improves culture, collaboration, competency and leadership. The last decade has seen rapid advances in connectivity, mo­bility, analytics, scalability and data, creating what some call the fourth industrial revolution, or Industry 4.0. With the help of the Industrial Internet of Things (IIoT), manufacturers have digitized operations, transforming efficiency, supply-chain performance and in­novation. This revolution has even created entirely new business models. This e-book gives manufacturers the tools to lead the Qual­ity 4.0 transformation – a transformation that raises traditional manufacturing to the next level. It teaches readers to use advanced technology, analytics and IIoT to strengthen the manufacturing process and bring it forward into a powerful digital age.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
With the support of SAS, the Internet of Things Institute developed the 2017 Internet of Things ROI Research Study to gather real-world insights, lessons learned and future guidance from current users of IoT technology and advanced analytics. This selective sample of IoT users offers valuable insights to both IoT innovators and organizations still waiting to see how the technology evolves before investing. Multiple business layers and functions have input into IoT decision making. Discover which layer was most critical to success for those organizations that have achieved the highest percentage of their targeted ROI. Learn about the main drivers of success for IoT users achieving higher returns. Lastly, the results highlight six primary factors that can undermine an IoT initiative and how they can be prevented.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Health insurers have long been plagued by issues of fraud, waste, abuse, error and corruption. Taking an enterprise approach to payment integrity – one that combines advanced data management and sophisticated analytics – can help payers detect and prevent fraud; effect positive change in how providers, employees and patients behave; and substantially reduce health care costs. Payers can achieve better outcomes when software support for the core disciplines of payment integrity run on a single platform.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
How much are fraud, error, waste and abuse costing your organization? Costs to insurers are huge – as much as 25 percent of payments made. But data management and analytics can save the day. This paper discusses how data can be used to predict and detect loss in all its forms.
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SAS
Published By: Esker     Published Date: Jun 29, 2017
Wasted time is wasted money — and accounts receivable (AR) departments can waste a lot of both with antiquated billing and collections methods. Download the new white paper‚ Winning the Billing & Collections Battle‚ to learn how your organization can overcome common obstacles in every phase of AR by: • Automating invoice delivery without format restrictions • Giving your customers self-service access to invoices • Modernizing post-sale collections interactions • Going beyond DSO with advanced KPIs and analytics With a complete AR management solution‚ time and money is on your side!
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accounts receivable management, invoice management, collections management, ar best practices, invoice portal, invoice delivery
    
Esker
Published By: SAS     Published Date: Oct 18, 2017
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
Published By: Hewlett Packard Enterprise     Published Date: Jul 12, 2016
Technology enables business transformation To thrive in today’s idea economy, small and midsize companies like yours are using technology to transform their business. Like your peers, you know that mobile applications, cloud-based solutions, and advanced analytics can help you increase productivity, reduce costs, and grow your business. Older servers, storage, and networking products weren’t built to handle the exploding amount of data that is being shared today. In order to take advantage of these modern applications, many companies have found that they need to close the gap between what their business demands and what their IT systems can deliver.
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best practices, business optimization, business management, application management, enterprise application, business intelligence, transformation
    
Hewlett Packard Enterprise
Published By: Cisco     Published Date: Jul 08, 2016
What You Will Learn: This document will identify the essential capabilities you need in an advanced malware protection solution, the key questions you should ask your vendor, and shows you how Cisco combats today’s advanced malware attacks using a combination of four techniques: • Advanced analytics • Collective global security threat intelligence • Enforcement across multiple form factors (networks, endpoints, mobile devices, secure gateways, and virtual systems) • Continuous analysis and retrospective security
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Cisco
Published By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
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pentaho, analytics, platforms, hadoop, big data, predictive analytics, networking, it management
    
Pentaho
Published By: Oracle CX     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle CX
Published By: SAP     Published Date: Dec 04, 2015
Download this whitepaper to see how advanced technologies such as big data, cloud computing, mobile devices, and enterprise access to in-memory platforms, predictive analytics, and planning software can help CFOs make better and more sophisticated use of data, influence decisions, and take practical, timely action.
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finance function, finance, cfo, big data, cloud computing, mobile, in-memory platforms, predictive analytics
    
SAP
Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
Creating predictive analytics from alternative data has become the current focus of the biggest quant trading firms in the industry The democratization of financial services data and technology, together with more intense competition, makes the needs of today’s market participants vastly different from those of previous generations. Firms must locate untapped sources of data for both public and non-public companies. This alternative data, such as payment data and other non-public information, from sources beyond the common channels, can be a predictive indicator of market performance; a difference maker in assisting firms as they develop models to evaluate their investments. By combining our unique data sets with advanced analytics, traders, analysts and managers can seek predictive signals and actionable information utilizing their own models. View our research report to learn how alternative data, our 'Information Alpha,' can help you earn differentiated investment returns.
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Dun & Bradstreet
Published By: GE Healthcare     Published Date: Aug 27, 2015
This paper will explore some of the market dynamics driving the financial volatility in healthcare and will explore how advanced analytics, with the right IT backbone and organizational competencies, can help organizations successfully identify ways to manage revenue cycle profitability.
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centricity business, financial management, analytics, revenue cycle, hospital billing, hospital finance, patient billing, rcm
    
GE Healthcare
Published By: FusionOps     Published Date: Jun 15, 2016
Bimodal capabilities, customer intimacy and advanced analytics can all be enabled by digital technologies, allowing supply chains to be both cost-effective and innovation-driven. This research explores the implications of these leading trends for chief supply chain officers.
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FusionOps
Published By: Infomatica     Published Date: Jul 15, 2015
Read “What it take to deliver advanced analytics” to discover: Why so many analytics projects suffer and how to avoid the most common missteps The seven symptoms of bad data and how to spot them The six principles of intelligent data management and how to put them into practice so you can become a decision-ready enterprise
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Infomatica
Published By: IBM     Published Date: Apr 05, 2016
Learn why advanced analytics tools are essential to sustain a competitive advantage. This white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics.
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ibm, predictive analytics, enterprise evolution, analytics tools, applied organization learning, knowledge management, enterprise applications, data management
    
IBM
Published By: IBM     Published Date: Oct 26, 2016
Predictive analytics has come of age. Organizations that want to build and sustain competitive advantage now consider this technology to be a core practice. In this white paper, author Eric Siegel, PhD, founder of Predictive Analytics World, reveals seven strategic objectives that can only be fully achieved with predictive analytics.
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ibm, predictive analytics, analytics tools, advanced analytics, enterprise applications, business technology, analytics, data science
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
Predictive analytics has come of age. Organizations that want to build and sustain competitive advantage now consider this technology to be a core practice. In this white paper, author Eric Siegel, PhD, founder of Predictive Analytics World, reveals seven strategic objectives that can only be fully achieved with predictive analytics. Read this paper to learn how your organization can more effectively: Compete – Secure the most powerful and unique competitive stronghold Grow – Increase sales and retain customers competitively Enforce – Maintain business integrity by managing fraud Improve – Advance your core business capacity competitively Satisfy – Meet today's escalating consumer expectations Learn – Employ today's most advanced analytics ....and finally, render your business intelligence and analytics actionable.
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predictive analytics, increase sales, customer retention, fraud management, consumer expectations
    
IBM
Published By: HP - Enterprise     Published Date: Jun 04, 2013
Hewlett-Packard (HP) is unique in this EMA Radar in its ability to combine two threads – a single analytic overlay as embodied in its Service Health Analyzer (SHA) product, and a broader suite solution optimized for HP to participate in all three use cases here with maximum functional impact. This is not entirely a black-and-white situation, as SHA does leverage and currently largely depends on integration with HP Business Service Management 9.1, which is itself a suite. But SHA can assimilate other third-party sources, checks out brilliantly in early-phase deployments in terms of time-to-value and analytic power, and is the lead reason for HP’s strong Value Leader showing in technical performance management.
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ema radar, performance analytics, apa, service health analyzer, business technology
    
HP - Enterprise
Published By: Teradata     Published Date: Jan 30, 2015
This TDWI Checklist Report discusses adjustments to DW architectures that real-world organizations are making today, so that Hadoop can help the DW environment satisfy new business requirements for big data management and big data analytics.
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data, data warehouse, hadoop, hadoop ecosystem, data architectures, data archiving, advanced analytics, data management
    
Teradata
Published By: Teradata     Published Date: Jan 30, 2015
Enterprise Hadoop Implementation with Teradata and Hortonworks
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ncr, big data, data warehouse, enterprise hadoop, hadoop implementation, teradata, hortonworks, performance data
    
Teradata
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