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data model

Results 276 - 300 of 373Sort Results By: Published Date | Title | Company Name
Published By: IBM     Published Date: May 27, 2014
If insurers want to succeed in today's digital world, they need to create experiences and business models that are orchestrated, symbiotic, contextual and cognitive.
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ibm, big data, insurance, digital insurer, business model, insurance industry, technology, integration, social business, it management
    
IBM
Published By: IBM     Published Date: Nov 19, 2014
Risk Management: General: Partially cloudy: the benefits of hybrid deployment models
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ibm, risk management, big data, data management, operational risk, event data, risk aware, risk solutions, hybrid deployment, deployment models
    
IBM
Published By: IBM     Published Date: Jul 19, 2016
Learn how IBM Cognos Analytics incorporates many governed discovery features, with which business users can easily expose the underlying data modelling of existing reports and modify it to an individual or departmental requirements
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ibm, ibm cognos analytics, analytics, business intelligence, business analytics
    
IBM
Published By: VSS Monitoring     Published Date: Aug 01, 2014
Learn how to leverage a big data model in the network monitoring domain and see how IT is shifting away from the long-term viability of the existing network monitoring model.
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networking, big data, network monitoring, optimization, data center, monitoring
    
VSS Monitoring
Published By: IBM     Published Date: Jul 01, 2015
This white paper discusses how enterprise analytics systems can assist provider organizations in building sustainable healthcare systems and achieving their vision for accountable care
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healthcare analytics, data blueprint, enterprise analytics systems, sustainable healthcare systems, mission-critical analysis, integrated data model, operational analytics
    
IBM
Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
The information security world is rich with information. From reviewing logs to analyzing malware, information is everywhere and in vast quantities, more than the workforce can cover. Artificial intelligence (AI) is a field of study that is adept at applying intelligence to vast amounts of data and deriving meaningful results. In this book, we will cover machine learning techniques in practical situations to improve your ability to thrive in a data driven world. With clustering, we will explore grouping items and identifying anomalies. With classification, we’ll cover how to train a model to distinguish between classes of inputs. In probability, we’ll answer the question “What are the odds?” and make use of the results. With deep learning, we’ll dive into the powerful biology inspired realms of AI that power some of the most effective methods in machine learning today. Learn more about AI in this eBook.
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artificial, intelligence, enterprise
    
BlackBerry Cylance
Published By: SAS     Published Date: Mar 06, 2018
The 2016 ACFE Report to the Nations on Occupational Fraud and Abuse analyzed 2,410 occupational fraud cases that caused a total loss of more than $6.3 billion.8 Victim organizations that lacked anti-fraud controls suffered double the amount of median losses. SAS’ unique, hybrid approach to insider threat deterrence – which combines traditional detection methods and investigative methodologies with behavioral analysis – enables complete, continuous monitoring. As a result, government agencies and companies can take pre-emptive action before damaging incidents occur. Equally important, SAS solutions are powerful yet simple to use, reducing the need to hire a cadre of high-end data modelers and analytics specialists. Automation of data integration and analytics processing makes it easy to deploy into daily operations.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
The most recent decade has seen rapid advances in connectivity, mobility, analytics, scalability, and data, spawning what has been called the fourth industrial revolution, or Industry 4.0. This fourth industrial revolution has digitalized operations and resulted in transformations in manufacturing efficiency, supply chain performance, product innovation, and in some cases enabled entirely new business models. This transformation should be top of mind for quality leaders, as quality improvement and monitoring are among the top use cases for Industry 4.0. Quality 4.0 is closely aligning quality management with Industry 4.0 to enable enterprise efficiencies, performance, innovation and business models. However, much of the market isn’t focusing on Quality 4.0, since many quality teams are still trying to solve yesterday’s problems: inefficiency caused by fragmented systems, manual metrics calculations, quality teams independently performing quality work with minimal cross-functional own
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SAS
Published By: IBM     Published Date: Sep 11, 2013
Through this whitepaper from IBM you will learn how to use predictive intelligence to make faster and better decisions
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spss, modeling, data mining, ibm, spss modeler, business analytst
    
IBM
Published By: IBM     Published Date: Sep 11, 2013
Learn how customer profitability analytics enables banks to analyze customer, account, product, and transaction data and apply costing models to determine a bank-wide view of profitability
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banks, customer profitability analytics, analytics, account, product, transaction data, costing models
    
IBM
Published By: IBM     Published Date: Nov 14, 2014
IBM SPSS Modeler is a powerful, versatile data and text analytics workbench. Learn how you can build accurate predictive models quickly and intuitively, without programming. So you can use data to understand the current state of your organization and get a view into the future.
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ibm, webinar, business intelligence, entity analytics, modeler, automated modeling, predictive intelligence, building models, spss modeler gold
    
IBM
Published By: Symantec     Published Date: Jul 11, 2017
The technology pendulum is always swinging. And chief information security officers must be prepared to swing with it—or get clocked. A look at recent history illustrates the oscillating nature of technology. In the 1980s, IBM mainframes dominated the landscape. In the ’90s, client-server computing came on the scene and data was distributed on personal computers. When the Web assumed predominance, the pendulum started to swing back to a centralized server. Then, just as quickly, mobile took the lead, with apps downloaded to workers’ devices—the new client server. Now, as mobile devices continue to populate the enterprise at a rapid rate, the IT model is changing again—to the provisioning of information on a just-what’s-needed, just-in-time basis from centralized servers consolidated in the cloud. The pendulum continues to swing and IT workloads are moving to the cloud en masse.
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cloud, security, data protection, data loss, information security
    
Symantec
Published By: IBM     Published Date: Aug 05, 2014
Watson Explorer provides organizations with a combined, trusted 360-degree view of both structured and unstructured data. The solution indexes information from unstructured data sources (PDFs, Microsoft SharePoint, flat files, social media, blogs and so on) as well as structured sources for search and discovery. Organizations can leverage their data in place, respecting existing security models when creating this virtual access point to all information. Watson Explorer requires trusted master data to ensure that links are accurate and reliable, so the end user can confidently leverage a holistic view of a customer or product.
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ibm, data, customer, watson explorer, master data, structured, it management
    
IBM
Published By: IBM     Published Date: Apr 09, 2015
As The Business Becomes Digital, Security Must Become Data-Centric S&R leaders of enterprises undergoing a digital transformation will soon realize that in order to adequately ensure customer protection and enable a digital workforce, S&R pros must abandon traditional perimeter-based security and put the focus on the data by embracing Forrester’s Zero Trust Model.
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data security, ibm, customer protection, digital workforce, zero trust model, security, it management
    
IBM
Published By: IBM     Published Date: Jun 07, 2016
The database you pick for your next application matters now more than ever. It can be difficult, and oftentimes impossible, to quickly join today's data into the relational model. Learn how a NoSQL database can act as a viable alternative to or compliment an existing relational database.
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ibm, nosql database, database, analytics, networking, enterprise applications
    
IBM
Published By: IBM     Published Date: Jul 12, 2016
Join us for a complimentary webinar with Mark Simmonds, IBM big data IT Architect who will talk with leading analyst Mike Ferguson of Intelligent Business Strategies about the current fraud landscape. They will discuss the business impact of fraud, how to develop a fraud-protection strategy and how IBM z Systems analytics solutions and predictive models can dramatically reduce your risk exposure and loss from fraud.
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ibm, z systems, fraud loss reduction, fraud management, fraud prevention, fraud analytics, roi, security
    
IBM
Published By: IBM     Published Date: Sep 30, 2016
Data is the lifeblood of today’s digital businesses; protecting it from theft, misuse, and abuse is the top responsibility of every S&R leader. Hacked customer data can erase millions in profits, stolen IP can destroy competitive advantage, and unnecessary privacy abuses can bring unwanted scrutiny and fines from regulators while damaging reputations. S&R pros must take a data-centric approach that ensures security travels with the data regardless of user population, location, or even hosting model; position data security and privacy capabilities as competitive differentiators; and build a new kind of customer relationship.
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ibm, security, data, privacy, forrester, forrester research
    
IBM
Published By: IBM     Published Date: Jul 17, 2018
As of May 25, 2018, organizations around the world—not just those based in the EU—need to be prepared to meet the requirements outlined within the EU General Data Protection Regulation (GDPR). Those requirements apply to any organization doing business with any of the more than 700 million EU residents, whether or not it has a physical presence in the EU. IBM® Security can help your organization secure and protect personal data with a holistic GDPR-focused Framework that includes software, services and GDPR-specific tools. With deep industry expertise, established delivery models and key insights gained from helping organizations like yours navigate complex regulatory environments, IBM is well positioned to help you assess your needs, identify your challenges and get your GDPR program up and running
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IBM
Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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Group M_IBM Q418
Published By: Group M_IBM Q418     Published Date: Sep 25, 2018
As of May 25, 2018, organizations around the world—not just those based in the EU—need to be prepared to meet the requirements outlined within the EU General Data Protection Regulation (GDPR). Those requirements apply to any organization doing business with any of the more than 700 million EU residents, whether or not it has a physical presence in the EU. IBM® Security can help your organization secure and protect personal data with a holistic GDPR-focused Framework that includes software, services and GDPR-specific tools. With deep industry expertise, established delivery models and key insights gained from helping organizations like yours navigate complex regulatory environments, IBM is well positioned to help you assess your needs, identify your challenges and get your GDPR program up and running.
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Group M_IBM Q418
Published By: Cisco     Published Date: Jul 11, 2016
If you need to deploy and scale applications faster to increase revenue, Cisco’s integrated infrastructure solutions can help you achieve your goals—and reduce risk. Technology transitions—such as cloud, mobility, big data, and the Internet of Things—bring together people, processes, data, and things to make resources and connections more valuable to your business. They also challenge the role of IT in the enterprise. For your IT department to stay relevant to your lines of business, it must deliver value faster and invest in innovation. Cisco Unified Computing System™ (Cisco UCS®) integrated infrastructure makes it possible to deliver Fast IT—a new IT model that transforms your data center infrastructure into an environment that is fast, agile, smart, and secure. You can break down the IT barriers that are holding your business back and create solutions that capture the value of new connections and information.
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Cisco
Published By: Hewlett-Packard     Published Date: Aug 02, 2013
When rack-mounted servers first appeared on the scene in the 1990s, they offered considerable advantages over the behemoth boxes they replaced. Their small, standardized footprint went a long way toward making data centers easier to manage. In the ensuing decades, form factor size and compute power have had an inverse relationship. Their universal standardization earned them the nickname “pizza box” servers, and it was a key driver of the scale-out computing model popular in the early 2000s. Populating a rack of eight servers and either clustering them or implementing failover from one to the other was far easier than previously possible.
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blade, servers, infrastructure, ip networks, local area networking, network management
    
Hewlett-Packard
Published By: IBM     Published Date: Apr 07, 2017
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization. This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solutions.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations, market research, model management
    
IBM
Published By: Mentor Graphics     Published Date: Apr 03, 2009
A powerful signal integrity analysis tool must be flexibility, easy to use and integrated into an existing EDA framework and design flow. In addition, it is important for the tool to be accurate enough. This report reviews a validation study for the Mentor Graphics HyperLynx 8.0 PI tool to establish confidence in using it for power integrity analysis.
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mentor graphics, pdn simulation, eda framework, mentor hyperlynx 8.0 pi, integrity analysis, virtual prototypes, esr, capacitor, power distribution network, vrm, voltage regulator module, signal, smas, analog models, backward crosstalk, capacitive crosstalk, controlling crosstalk, correct emc problems, correct emi problems, cross talk
    
Mentor Graphics
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