advanced analytics

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Published By: Adobe     Published Date: Aug 02, 2017
With the advanced analytics capabilities in Adobe Analytics and the testing and targeting capacity of Adobe Target, it’s easier than ever to realise the potential of data-driven marketing. From creating a complete view of each customer across touchpoints and along their journey, to using predictive analytics, advanced anomaly detection and machine learning to understand behaviours and needs, you can use data to plan, create and optimise the experiences that matter to you and your customers.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
Adobe
Published By: McAfee     Published Date: Apr 14, 2014
Beyond the basics in a next generation firewall, to protect your investment you should demand other valuable features: intrusion prevention, contextual rules, advanced evasion analytics, secured access control, and high availability.
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next generation firewall, intrusion prevention systems, firewall, contextual security, advanced evasion detection, advanced evasion techniques, security, it management
    
McAfee
Published By: McAfee     Published Date: Apr 25, 2014
McAfee® Threat Intelligence Exchange and the McAfee Security Connected Platform can help integrate workflows and data to overcome siloed operations and shift the security model to agile, intelligent threat prevention. This paper describes three use cases to illustrate the benefits.
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advanced malware, security, suspicious files, dynamic sandboxing, static analytics, threat prevention, mcafee network security, mcafee web gateway, mcafee email gateway, it management
    
McAfee
Published By: Microsoft Azure     Published Date: Apr 11, 2018
Developing for and in the cloud has never been more dependent on data. Flexibility, performance, security—your applications need a database architecture that matches the innovation of your ideas. Industry analyst Ovum explored how Azure Cosmos DB is positioned to be the flagship database of internet-based products and services, and concluded that Azure Cosmos DB “is the first to open up [cloud] architecture to data that is not restricted by any specific schema, and it is among the most flexible when it comes to specifying consistency.” From security and fraud detection to consumer and industrial IoT, to personalized e-commerce and social and gaming networks, to smart utilities and advanced analytics, Azure Cosmos DB is how Microsoft is structuring the database for the age of cloud. Read the full report to learn how a globally distributed, multi-model data service can support your business objectives. Fill out the short form above to download the free research paper.
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Microsoft Azure
Published By: AWS     Published Date: Dec 17, 2018
Watch this webinar to learn best practices from Zaloni for creating flexible, responsive, and cost-effective data lakes for advanced analytics that leverage Amazon Web Services (AWS).
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AWS
Published By: LogRhythm     Published Date: Feb 22, 2018
Security and risk management leaders are implementing and expanding SIEM to improve early targeted attack detection and response. Advanced users seek SIEM with advanced profiling, analytics and response features.
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LogRhythm
Published By: McAfee     Published Date: Mar 31, 2017
Overwhelmed by the volume of security intelligence and alerts, human analysts need machine learning to augment and accelerate efforts. Machine learning moves security analytics from diagnostic and descriptive to prescriptive and proactive, leading to faster and more accurate detection.
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machine learning, advanced analytics, advanced threats, sandbox, zero-day, malware, mcafee labs, dynamic endpoint
    
McAfee
Published By: SwellPath     Published Date: Sep 04, 2012
This guide provides the framework to build a successful analytics foundation in your organization, and shows you how to create an effective analytics measurement program that provides actionable insights and results driven recommendations.
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google analytics, marketing analytics, ecommerce analytics, analytics strategy, web analytics, analytics implementation, google analytics consulting, measurement strategy, analytics program, key performance indicators, campaign reporting, analytics best practices, website optimization, kpis, website optimization, advanced google analytics, dashboards, scorecards, social analytics, analytics training
    
SwellPath
Published By: SAS     Published Date: Apr 25, 2017
Artificial intelligence and related forms of advanced analytics hold enormous potential for marketers to expand and deepen customer intelligence, improve business processes, and deliver engaging customer experiences. But many marketing organizations are just getting their feet wet in leveraging these technologies. To learn about the opportunities and challenges, IIA spoke with Analise Polsky, Business Solutions Manager, SAS Best Practices and Jonathan Moran, Principal Product Marketing Manager, SAS Customer Intelligence Solutions.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
"How do you make your brick-and-mortar stores as smart as your website – so when customers walk in the door, you recognize them and cater to their individual tastes? What’s the key to making in-store shopping as frictionless for your customer as online shopping? Read this research summary from the International Institute for Analytics to get started. You’ll learn how to use analytics to gain advanced insight from the Internet of Things: tracking chips, in-store infrared traffic monitors, interactive kiosks and customer mobile devices, to name a few. With analytics, you’ll identify who’s walking in your store, understand their behavior and preferences, and create engaging experiences for your connected customers at every turn. "
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SAS
Published By: ClearSaleing     Published Date: Aug 27, 2010
Read this report to learn how you can benefit from implementing better advertising analytics for your company.
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forrester, consulting, conversion rates, tei, advertising analytics, marketing analytics, conversions, attribution, campaigns, channels, advertising, marketing, profit, roi, tracking software, attribution management, paid search, display, shopping engine, seo
    
ClearSaleing
Published By: IBM     Published Date: Apr 29, 2014
For banks, mining data from social media can be a significant way to gain insights into customer mindsets and behavior, but effectively and accurately capturing and processing this unstructured data to gain useful customer insight requires sophisticated tools and advanced analytics.
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ibm, banking, data mining, social media, consumer insights, business analytics, social business, business technology
    
IBM
Published By: SAP     Published Date: Nov 22, 2011
Analytics has moved from the specialty of a dedicated few to a necessity for broad groups of business professionals to do their job. This white paper considers the use of analytics and business intelligence in the banking industry for improving decision making and the benefits of prebuilt analytic applications for achieving this objective across many functions in a banking organization.
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idc, finance, technology, business, banking, analytics, decision making, business technology
    
SAP
Published By: IBM     Published Date: Jan 20, 2015
Deploying a flexible, user-friendly framework for cloud-based risk modeling across multiple asset classes.
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risk analytics, cloud-based risk modeling, asset classes, asset management, portfolio management, security, it management, knowledge management, enterprise applications
    
IBM
Published By: IBM     Published Date: Jul 23, 2015
Predict better academic outcomes with IBM SPSS Decision Management for Student Performance.
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predictive analytics, performance management, student performance, spss, decision management, intervention measures, graduation rates, advanced placement courses, data analytics
    
IBM
Published By: SAS     Published Date: Mar 06, 2018
There is a lot of excitement in the market about artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Although many of these technologies have been available for decades, new advancements in compute power along with new algorithmic developments are making these technologies more attractive to early adopter companies. These organizations are embracing advanced analytics technologies for a number of reasons including improving operational efficiencies, better understanding behaviors, and gaining competitive advantage.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
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. With the right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
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SAS
Published By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
These emerging technologies and solutions certainly are not unique to financial services. But Stewart, a business director of security intelligence solutions within the SAS Security Intelligence Practice, sees particular interest and application in AML circles. "There remain a good number of manual processes within financial crimes departments in financial institutions, and AI can help automate some of those rote tasks such as document review or alert triage," he says. "Due to investments in technology, there is a lower barrier of entry for midsized institutions. "And finally, there's this anxiety over the unknown - those risks they are not able to detect, that may be hidden using traditional techniques - so they're hoping that more advanced, unsupervised learning techniques can be used to identify those edge cases or behaviors that are out of norm." In an interview about analytics and the AML paradigm shift, Stewart discusses: • The new industry intrigue with artificial intelligence a
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SAS
Published By: SAS     Published Date: Mar 06, 2018
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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SAS
Published By: SAS     Published Date: Apr 04, 2018
“Fixing health care” is an urgent and pervasive priority for governments, businesses and citizens alike. Within many countries, costs are out of control, resulting in reduced access to quality care for those who need it, higher taxes and/or insurance costs for companies and citizens – and unfortunately, poorer health outcomes.
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SAS
Published By: SAS     Published Date: Jun 06, 2018
Today’s consumers expect immediate, personalized interactions. To meet these expectations, companies must differentiate their brands through timely, targeted and tailored customer experiences based on real-time data analytics. This report, sponsored by SAS, Intel and Accenture and conducted by Harvard Business Review Analytic Services, looks at how businesses are using advanced customer data analytics, along with real-time analytics and real-time marketing, to enhance their customers’ experiences. Learn why organizations that place a high value on real-time capabilities still struggle to achieve them, what companies can do to ensure success as they adopt and implement real-time analytics solutions, and what benefits successful companies are already seeing.
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SAS
Published By: IBM     Published Date: Jul 27, 2015
Read this issue to learn how to tap into the massive amounts of data and information across your organization.
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cloud-based data management, sustainability energy, future of energy, data analytics, utility analytics, grid optimization, advanced analytics integration, cloud-based services
    
IBM
Published By: IBM     Published Date: Nov 20, 2015
Discover how proficient your organization is at using advanced analytics to transform the way you do business. Take the assessment.
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ibm, energy, utilities, analytics, business technology
    
IBM
Published By: IBM     Published Date: Apr 23, 2013
Profitability analysis is important to all companies. But in times of economic uncertainty, it becomes even more critical because organizations need a comprehensive and forwardlooking view of profitability to ensure that they can remain financially viable, whatever the economic circumstances. For companies to be successful, they need automated systems that enable interactive profitability analysis that can be shared across a broad swath of users. They also need robust, advanced analytics, to provide detailed granular metrics for assessing profitability and measuring performance. IBM offers solutions that can meet those needs.
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profitability, analysis, finance, projection, prediction, analytics, automation, metrics
    
IBM
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