analytical

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Published By: SAS     Published Date: Sep 05, 2019
Envision this situation at a growing bank. Its competitive landscape demands an agile response to evolving customer needs. Fortunately, analytically minded professionals in different divisions are seeing results that positively affect the bottom line. • A data scientist in the business development team analyzes data to create customized • experiences for premium customers. • A digital marketer tracks and influences the customer journey for prospective • mortgage customers. • A risk analyst builds risk models for the bank’s loan portfolios. • A data analyst examines data about local customers. • A technical architect defines a new system to protect bank data from internal and • external cyberthreats. • An application developer builds a new mobile app for online customer portfolio • management. Between them, these employees might be using more than a dozen packages for analytics and data management.
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SAS
Published By: MicroStrategy     Published Date: Aug 28, 2019
Over the last decade, the enterprise analytics landscape has dramatically transformed. Vendors have come and gone, and platforms have continually expanded their offerings to include new functionality and keep pace with the demands of the businesses they serve. Originally envisioned as an IT-centric tool for enterprise reporting, analytics today has evolved into a business solution—empowering a range of users across every line of business, including front-line employees, field personnel, and executives. The rise of self-service analytics over the past decade has played a key role in promoting a data-driven mindset within every business function. However, this practice is limited to a skilled few. The vast majority of business professionals lack the time, analytical skills, or inclination to conduct their own analyses, and fail to effectively use analytics on a day-to-day basis. The result? Despite decades of investments, BI adoption at most organizations remains at 30%. The failure of e
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MicroStrategy
Published By: MicroStrategy     Published Date: Aug 28, 2019
Why HyperIntelligence? Today, despite massive investments in data, IT infrastructure, and analytics software, the adoption of analytics continues to lag behind. In fact, according to Gartner, most organizations fail to hit the 30% mark. That means that more than 70% of people at most organizations are going without access to the critical information they need to perform to the best of their abilities. What’s stopping organizations from breaking through the 30% barrier and driving the pervasive adoption of intelligence? Simple. The majority of existing tools only cater to users who are naturally analytically inclined—the analysts, data scientists, and architects of the world. The other 70%—the people making the operational decisions daily within a business—simply lack the time, skill, or desire to seek out data and intelligence on their own. HyperIntelligence helps organizations operationalize their existing investments and arm everyone across the organization with intelligence. Whether
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MicroStrategy
Published By: TIBCO Software     Published Date: Aug 20, 2019
How we fuel our vehicles, heat our homes, and power our industries is undergoing fundamental change. Well-deployed but inefficient technologies, such as internal combustion engine cars and oil/gas boilers are being replaced with electrified and higher-efficiency alternatives. And renewables such as sunlight, wind, thermal, and others, supported by next generation battery storage, are fueling an evergreater share of energy demand.
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renewable energy, oil&gas, connected intelligence, real-time data, analytical insights, information technology
    
TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
What if you could use just one platform to detect all types of major financial crimes? One platform to handle the analytical tasks of fraud detection, including: Data processing and aggregation Data visualization Statistical/mathematical/machine learning modeling Batch/real-time scoring One platform that could successfully reduce complex and time-consuming fraud investigations by combining extremely different domains of knowledge including Business, Economics, Finance, and Law. A platform that can cover payments, credit card transactions, and know your customer (KYC) processes, as well as similar use cases like anti-money laundering (AML), trade surveillance, and crimes such as insurance claims fraud. Learn more about TIBCO's comprehensive software capabilities behind tackling all these types of fraud in this in depth whitepaper.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
The Insurance industry continues to undergo significant transformation, with new technologies, business models, and competitors entering the market at an increasing rate. To be successful in attracting and retaining the most valuable customers, insurance companies must innovate and increase the speed at which they respond to customer demands. Traditionally, the insurance software market was dominated by a handful of specialist vendors with products that were initially expensive, difficult to deploy, costly to maintain, and did not provide the speed needed for today’s market. Now there has been a shift away from these “black box” applications to platforms that allow insurers to make their algorithmic IP available to business users, allowing much faster response to business demands. The algorithmic platform approach also comes at a fraction of the cost of black box solutions, while delivering advanced analytical techniques like Machine Learning and Artificial Intelligence (AI).
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TIBCO Software
Published By: Forcepoint     Published Date: Jun 06, 2019
In a recent study, IDC analyzed the business value and benefits of supporting network operations with Forcepoint NGFW solutions. The research included interviews with eight organizations relying upon Forcepoint’s NGFW to connect and protect their networks and business operations. IDC created a model based upon their analysis to identify the costs and real benefits of deploying Forcepoint NGFW. The highlights of this analytical model are captured in their Business Value Snapshot; and the complete results are available for download now in the IDC Quantifying the Operational and Security Results of Switching to Forcepoint NGFW Whitepaper. Download the Snapshot now Download the IDC Whitepaper now to learn how the eight organizations surveyed realized improved efficiency, availability and security with Forcepoint NGFW, as well as a return of cost in only seven months and an average 5-year ROI of 510%.
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Forcepoint
Published By: Yokogawa Corporation of America     Published Date: May 27, 2019
An Analytical Approach to Improving Safety & Efficiency Fired heaters are the largest energy consumer in the manufacturing sector, and represent a tremendous opportunity for energy savings. However, energy efficiency is not the only concern for fired heaters. Compliance and safety are continuous challenges. In this eBook we explain how to improve fired heaters safety and efficiency by controlling combustion using TDLS technology. Download it now and learn: • The 4 top industry challenges related to fired heaters • How to efficiently and safely manage combustion • How TDLS technology can improve operational excellence in fired heaters Yokogawa's privacy notice for downloading contents.
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Yokogawa Corporation of America
Published By: HERE Technologies     Published Date: May 22, 2019
Operational readiness depends on rich location data. When managing logistics and tracking high-value assets, there is no room for error and our new data-driven world demands richer, smarter advanced mapping and navigation services. The 2018 Counterpoint Research Location Ecosystems Update compared 16 location platform vendors—including Google, TomTom and Mapbox—and it named HERE the “undisputed leader” in location based services. Counterpoint recognized HERE for its integrated analytical capability and commitment to open partnerships, allowing for custom operational requirements and a truly mobile location intelligence platform. See how HERE provides the industry leading tools and expertise to process that data—streamlining the logistics supply chain, boosting responsiveness, and guaranteeing mission success.
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mapping, defence, location data.
    
HERE Technologies
Published By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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Group M_IBM Q2'19
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
In this paper, we focus on the DWA and how it has evolved over the years since its introduction. The XDW architecture is then described, in which the need to maintain the data warehouse is documented while adding new components and capabilities to extend the analytical capabilities. This section also discusses the appropriate usage of appliances within the XDW. The rest of the paper covers the benefits from implementing the DWA, the selection considerations for them and what the future holds for them.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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Group M_IBM Q119
Published By: SAS     Published Date: Dec 20, 2018
Think of the self-service things you use in a day. Gas pumps. ATMs. Online apps for shopping. They’re convenient and easy to use. People choose what they want, when they want – without involving others in their minute-to-minute decisions. What if your organization could treat data discovery and analytics the same way? SAS has combined two of its visual solutions to do just that. SAS Visual Analytics and SAS Visual Statistics share the same web-based interface to provide self-service data exploration and easy-to-use interactive predictive analytics in a collaborative environment. This white paper takes a look at this convergence and outlines how these products can be used together so that everyone, even nontechnical users, can investigate data on their own, create analytical models and uncover new insights that drive competitive differentiation. Your analytics journey just got a lot easier.
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SAS
Published By: TIBCO Software     Published Date: Nov 12, 2018
The insurance industry stands on the precipice of change, with waves of innovation and disruption driving new possibilities across all departments, including pricing, underwriting, claims, and fraud. This webinar recording of a live panel debate is ideal for insurance professionals wanting to understand how best to unlock the possibilities created by advanced analytical techniques such as Artificial Intelligence (AI), Machine Learning (ML), and others. This TIBCO and Marketforce webinar on “The Fourth Industrial Revolution in Insurance” includes speakers Ian Thompson, chief claims officer at Zurich; David Williams, chief underwriting officer at AXA; and Clare Lunn, GI fraud director at LV=. The panel discusses: Moving towards the algorithmic insurer: the opportunities created by AI and ML How insurers can become more agile in the face of new innovations and disruptive technologies How the industry can turn structured and unstructured data into insights
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agile insurance, customer experience, digital initiatives, analytical techniques
    
TIBCO Software
Published By: TIBCO Software     Published Date: Oct 03, 2018
The Insurance industry continues to undergo significant transformation, with new technologies, business models, and competitors entering the market at an increasing rate. To be successful in attracting and retaining the most valuable customers, insurance companies must innovate and increase the speed at which they respond to customer demands. Traditionally, the insurance software market was dominated by a handful of specialist vendors with products that were initially expensive, difficult to deploy, costly to maintain, and did not provide the speed needed for today's market. Now there has been a shift away from these "black box" applications to platforms that allow insurers to make their algorithmic IP available to business users, allowing much faster response to business demands. The algorithmic platform approach also comes at a fraction of the cost of black box solutions, while delivering advanced analytical techniques like Machine Learning and Artificial Intelligence (AI).
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artificial intelligence, machine learning, dynamic pricing, predictive claims, real-time fraud, contextual customer experience, operational effectiveness
    
TIBCO Software
Published By: TIBCO Software     Published Date: Sep 12, 2018
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution. Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze. Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform. Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing: • Reduced downtime • Minimized surplus and defects • Deep insights • End-to-end real-time visibility
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internet of things, connected ecosystem, big data, operations monitoring, process control, analytical techniques
    
TIBCO Software
Published By: Carbon Black     Published Date: Aug 14, 2018
Threat hunting is the proactive technique that’s focused on the pursuit of attacks and the evidence that attackers leave behind when they’re conducting reconnaissance, attacking with malware, or exfiltrating sensitive data. Instead of just hoping that technology flags and alerts you to the suspected activity, you apply human analytical capacity and understanding about environment context to more quickly determine when unauthorized activity occurs. This process allows attacks to be discovered earlier with the goal of stopping them before intruders are able to carry out their attack objectives.
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Carbon Black
Published By: IBM     Published Date: Jul 09, 2018
As the information age matures, data has become the most powerful resource enterprises have at their disposal. Businesses have embraced digital transformation, often staking their reputations on insights extracted from collected data. While decision-makers hone in on hot topics like AI and the potential of data to drive businesses into the future, many underestimate the pitfalls of poor data governance. If business decision-makers can’t trust the data within their organization, how can stakeholders and customers know they are in good hands? Information that is not correctly distributed, or abandoned within an IT silo, can prove harmful to the integrity of business decisions. In search of instant analytical insights, businesses often prioritize data access and analysis over governance and quality. However, without ensuring the data is trustworthy, complete and consistent, leaders cannot be confident their decisions are rooted in facts and reality
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IBM
Published By: IBM     Published Date: Jul 05, 2018
Scalable data platforms such as Apache Hadoop offer unparalleled cost benefits and analytical opportunities. IBM helps fully leverage the scale and promise of Hadoop, enabling better results for critical projects and key analytics initiatives. The end-to- end information capabilities of IBM® Information Server let you better understand data and cleanse, monitor, transform and deliver it. IBM also helps bridge the gap between business and IT with improved collaboration. By using Information Server “flexible integration” capabilities, the information that drives business and strategic initiatives—from big data and point-of- impact analytics to master data management and data warehousing—is trusted, consistent and governed in real time. Since its inception, Information Server has been a massively parallel processing (MPP) platform able to support everything from small to very large data volumes to meet your requirements, regardless of complexity. Information Server can uniquely support th
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IBM
Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
The 21st century marks the rise of artificial intelligence (AI) and machine learning capabilities for mass consumption. A staggering surge of machine learning has been applied for myriad of uses — from self-driving cars to curing cancer. AI and machine learning have only recently entered the world of cybersecurity, but it’s occurring just in time. According to Gartner Research, the total market for all security will surpass $100B in 2019. Companies are looking to spend on innovation to secure against cyberthreats. As a result, more tech startups today tout AI to secure funding; and more established vendors now claim to embed machine learning in their products. Yet, the hype around AI and machine learning — what they are and how they work — has created confusion in the marketplace. How do you make sense of the claims? Can you test for yourself to know the truth? Cylance leads the cybersecurity world of AI. The company spearheaded an innovation revolution by replacing legacy antivirus software with predictive, preventative solutions and services that protect the endpoint — and the organization. Cylance stops zero-day threats and the most sophisticated known and unknown attacks. Read more in this analytical white paper.
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cylance, endpoint, protection, cyber, security
    
BlackBerry Cylance
Published By: Monetate     Published Date: Jun 27, 2018
A robust testing and optimization program is critical to the success of any travel and hospitality online bookings and reservations engine. Discover how personalization can help you drive impact using your pre-exisiting creative and analytical assets. In this handy guide you’ll learn how Monetate’s testing, segmenting and optimization program helps travel and hospitality companies: • Recognize visitors and customers across devices to deliver connected experiences. • Optimize bookings funnels to raise bookings conversion rates and revenues. • Segment customers to deliver truly customized content. • Decrease the customers time to purchase by serving the right trip, excursion or reservation.
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Monetate
Published By: IBM     Published Date: Jun 04, 2018
"What would you do if you didn’t have to rely on disparate analytics solutions to meet the needs of business users while following the rules of IT? View this 'Charting Your Analytical Future' webinar to learn about a world of innovation and independence for users that does not limit the confidence and controls of IT. With the cognitive-guided self-service features available in IBM business analytics solutions, more users than ever before can get the answers they need. Next-generation business analytics capabilities make it possible to access relevant data, prepare it for analysis and understand performance. But it doesn’t stop there. Users can package the results in a visually-appealing format and share them throughout the organization. Don’t miss this opportunity to hear how you can: * Benefit from advanced analytics without the complexity * Operationalize insights and dashboards from a collection of trusted data sources * Tell your story with rich visualizations and geospati
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business analytics, analytics solutions
    
IBM
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
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