analytical

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Published By: NetApp     Published Date: May 29, 2018
The analytics and BI platform market's multiyear shift of focus from IT-led reporting to business-led self-service analytics is now mainstream. Data and analytics leaders should invest in modern platforms for greater accessibility, agility and analytical insight from a diverse range of data sources.
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NetApp
Published By: SAS     Published Date: May 24, 2018
Information on artificial intelligence (AI) is flooding the market, media and social channels. Without doubt, it’s certainly a topic worth the attention. But, it can be difficult to sift through market hype and grandiose promises to understand exactly how AI can be applied in practical and reliable solutions. Like most technological advances, incorporating new technology into business processes requires significant leadership and effective direction that all stakeholders can easily understand. Great leaders become great by balancing strategy with tactics, future vision with current reality and strengths with weaknesses – all with the goal of accomplishing a clearly defined objective. Great leaders also understand that people are the most valuable resources within their organization. To drive and inspire their success, you must optimize strengths while recognizing inherent weaknesses. Many of our daily human experiences and interactions involve machines or devices of some sort. Technolo
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SAS
Published By: IBM     Published Date: May 04, 2018
A dversaries, and cybercriminal organizations in particular, are building tools and using techniques that are becoming so difficult to detect that organizations are having a hard time knowing that intrusions are taking place. Passive techniques of watching for signs of intrusion are less and less effective. Environments are complicated, and no technology can find 100 percent of malicious activity, so humans have to “go on the hunt.” 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 t
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IBM
Published By: Tableau     Published Date: Apr 13, 2018
In this whitepaper, discover the benefits of expanding your analytics toolkit. Combine Excel’s data collection and management capabilities with Tableau’s intuitive, analytical power to transform your raw data into actionable insights. Focus on the questions that take your data beyond the spreadsheet. Read more at about this partnership.
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Tableau
Published By: Carbon Black     Published Date: Apr 11, 2018
Adversaries, and cybercriminal organizations in particular, are building tools and using techniques that are becoming so difficult to detect that organizations are having a hard time knowing that intrusions are taking place. Passive techniques of watching for signs of intrusion are less and less effective. Environments are complicated, and no technology can find 100 percent of malicious activity, so humans have to “go on the hunt.” 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 t
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Carbon Black
Published By: Carbon Black     Published Date: Apr 10, 2018
A dversaries, and cybercriminal organizations in particular, are building tools and using techniques that are becoming so difficult to detect that organizations are having a hard time knowing that intrusions are taking place. Passive techniques of watching for signs of intrusion are less and less effective. Environments are complicated, and no technology can find 100 percent of malicious activity, so humans have to “go on the hunt.” 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 t
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Carbon Black
Published By: SAS     Published Date: Mar 06, 2018
Information on artificial intelligence (AI) is flooding the market, media and social channels. Without doubt, it’s certainly a topic worth the attention. But, it can be difficult to sift through market hype and grandiose promises to understand exactly how AI can be applied in practical and reliable solutions. Like most technological advances, incorporating new technology into business processes requires significant leadership and effective direction that all stakeholders can easily understand.
Tags : 
    
SAS
Published By: SAS     Published Date: Mar 06, 2018
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated drive as you read the morning news. We are getting very close to that kind of scenario, and companies like Ford expect to have production vehicles in the latter part of 2020. Driverless cars are just one popular example of machine learning. It’s also used in countless applications such as predicting fraud, identifying terrorists, recommending the right products to customers at the right time, and correctly identifying medical symptoms to prescribe appropriate treatments. The concept of machine learning has been around for decades. What’s new is that it can now be applied to huge quantities of data. Cheaper data storage, distributed processing, more powerful computers and new analytical opportunities have dramatically increased interest in machine learning systems. Other reasons for the increased momentum include: maturing capabilities with methods and algorithms refactored to run in memory; the
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SAS
Published By: SAS     Published Date: Mar 06, 2018
Business intelligence has come a long way ? from assistance with report generation to self-service platforms for discovery and analytical insight. As technological capabilities and business aptitude with information continue to advance, the next generation of BI will be even more capable and valuable to the enterprise. To discuss today’s success factors and tomorrow’s opportunities, IIA spoke with Rick Styll, Senior Manager, Visual Analytics Product Management at SAS, and Tapan Patel, Principal Product Marketing Manager at SAS.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
Better health care at lower costs, for everyone – how do health care providers get there? Understanding the gaps in patient care, patient needs, and the geographic distribution of the patient population are important elements to consider when making decisions about improving the quality of care and reducing its costs. To effectively analyze gaps in patient care, the data needs to be in a single place or system. However, in many organizations, data is spread across a myriad of spreadsheets and database systems. Data not organized for visual exploration and coherent analysis isn’t useful for decision making. Hence the need for visually appealing and scalable analytical tools to help organizations be more efficient, effective and economically successful.
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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
Enhanced regulatory pressure requires continuous evaluation of your bank’s risks. To meet these demands, the AML industry has turned to analytical/statistical methodologies to: • Improve monitoring programs. • Reduce false-positive alerts. • Increase monitoring coverage. • Reduce the rapidly escalating financial cost of maintaining AML programs.
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SAS
Published By: Group M_IBM Q1'18     Published Date: Feb 15, 2018
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
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analytics assessment, business decisions, predictive analytics, analytics
    
Group M_IBM Q1'18
Published By: SAS     Published Date: Jan 17, 2018
This RSR custom research report explores the impact of omnichannel methods on merchandising, marketing and the supply chain; specifically, what analytical capabilities address the challenges that omnichannel selling and fulfillment pose for retailers. Consumers today routinely begin their shopping journeys online, but complete their purchases in nearby stores, in their “home” stores or delivered directly to their doors. Retail analytics enables organizations to capture data from their customers' journeys. Retailers that successfully deliver relevant omnichannel experiences while gaining a more sophisticated understanding of demand (where and how it is initiated) will enhance their brands’ value and create compelling and profitable customer relationships.
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SAS
Published By: Dell and Nutanix     Published Date: Jan 16, 2018
Because many SQL Server implementations are running on virtual machines already, the use of a hyperconverged appliance is a logical choice. The Dell EMC XC Series with Nutanix software delivers high performance and low Opex for both OLTP and analytical database applications. For those moving from SQL Server 2005 to SQL Server 2016, this hyperconverged solution provides particularly significant benefits.
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data, security, add capacity, infrastructure, networking, virtualization, dell
    
Dell and Nutanix
Published By: Anaplan     Published Date: Nov 27, 2017
"The pressure on sales to meet and exceed ever-increasing revenue targets is higher than ever before. At the heart of this challenge lies a complex analytical and modeling problem that involves data spread across many rigid–and usually disconnected–systems, teams, and geographies. Leading companies handle this problem by focusing first on creating a sales performance plan that is data-driven and tied to business objectives. The research report conducted by Harvard Business Review provides you with how today's sales executives: • Overcome technology weaknesses to uncover sophisticated analytics • Change ingrained, cultural tendances of sales organizations • Adopt dynamic practices to respond to change quicker"
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Anaplan
Published By: Medidata     Published Date: Nov 10, 2017
Founded by physicians committed to advancing medical science, Worldwide Clinical Trials is out to change how the world experiences CROs. From early phase and bioanalytical sciences through late phase and post-approval, they provide full-service drug development services across a range of therapeutic areas, including neuroscience, cardiovascular diseases, immune-mediated inflammatory disorders (IMID) and rare diseases.
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Medidata
Published By: Pure Storage     Published Date: Nov 02, 2017
The evolution of genomics in recent decades has seen the volume of sequencing rise dramatically as a result of lower costs. Massive growth in the quantities of data created by sequencing has greatly increased analytical challenges, and placed ever-increasing demands on compute and storage infrastructure. Researchers have leveraged high-performance computing environments and cluster computing to meet demands, but today even the fastest compute environments are constrained by the lagging performance of underlying storage.
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big data, simple, fast, multi dimensional performance, eliminate complexity, lower tco, innovation
    
Pure Storage
Published By: SAS     Published Date: Oct 18, 2017
Are you thinking about adding artificial intelligence to your organization? It’s certainly a hot topic and worth the attention. This paper outlines the SAS approach to AI and explains key concepts. It also provides process and implementation tips if you are considering adding AI technologies to your business and analytical strategies.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications such as driverless cars. This paper, based on presentations by SAS Data Scientist Wayne Thompson, introduces key machine learning concepts and describes SAS solutions that enable data scientists and other analytical professionals to perform machine learning at scale. It tells how a SAS customer is using digital images and machine learning techniques to reduce defects in the semiconductor manufacturing process.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
With enhanced regulatory pressure, banks must continuously evaluate their risks. To meet these demands, the AML industry has turned to analytical/statistical methodologies to reduce false-positive alerts, increase monitoring coverage and reduce the rapidly escalating financial cost of maintaining their AML programs. An effective AML transaction monitoring strategy includes segmenting the customer base by analyzing customer activity and risk characteristics in order to monitor them more effectively. This paper explains how to blend both quantitative and qualitative methods to tune scenarios to identify the activity that poses the most risk to the bank.
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SAS
Published By: IBM     Published Date: Oct 17, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive (MiFID2). Many of these new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data
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IBM
Published By: IBM     Published Date: Oct 03, 2017
Many new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data. To keep pace with regulatory changes, many banks will need to reapportion their budgets to support the development of new systems and processes. Regulators continually indicate that the banks must be able to provide, secure and deliver high-quality information that is consistent and mature.
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data aggregation, risk reporting, bank regulation, enterprise, reapportion budgets
    
IBM
Published By: Alteryx, Inc.     Published Date: Sep 06, 2017
Organizations that want to apply consistent data management, governance and security practices across their organization can learn a lot from Ford Motor Company. Data-driven decision making led Ford Motor Company to perfect the vehicle assembly line in 1913. A century later, Ford had more than 4,600 data sources, and a wide range of analytical tools, methods, and processes in use throughout the company, and needed a more strategic approach to decision-making.
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Alteryx, Inc.
Published By: IBM APAC     Published Date: Aug 25, 2017
The world of business analytics is evolving rapidly, and while there are multiple emerging trends of note, two stand out as particularly impactful. First, there is an expanding and increasingly diverse audience of users that are becoming more analytically active. From mid-level Line-of-Business staff to senior executives on mahogany row, more users in more job functions are taking an increased level of ownership in the insight that fuels their decisions and the underlying data that supports that insight.
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data integration, data security, data optimization, data virtualization, database security
    
IBM APAC
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