analytics

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Published By: TIBCO Software GmbH     Published Date: Jan 22, 2019
The Internet of Things (IoT) didnt just connect everything everywhere; It laid the groundwork for the next industrial revolution. Connected devices sending data was only one achievement of the IoTbut 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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TIBCO Software GmbH
Published By: Brightcove     Published Date: Jul 01, 2011
Brightcove Video Cloud gives you everything you need to deliver professional quality video to audiences on every screen.
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brightcove, free trial, publishing online video, content, viewers, audience attention, online video advisor, industry-leading tools, analytics, content delivery, content integration, content management system
    
Brightcove
Published By: Collaborative Consulting     Published Date: Dec 20, 2013
Social, Mobile, Analytics and Cloud (SMAC), have broad potential to provide huge business value, while simultaneously presenting potentially overwhelming challenges. The rapid technology changes supporting SMAC and the overall complexity involved demand a systematic approach to building out your SMAC capability.
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collaborative consulting, creating opportunities, driving disruption, social, mobile, analytics, cloud, infrastructure, elastic computing capacity, cloud computing, social network, mobile web, wireless data networks, drive change, wireless, business analytics
    
Collaborative Consulting
Published By: Acxiom Corporation     Published Date: Mar 12, 2014
In July 2013 Acxiom commissioned Forrester Consulting to evaluate how companies use the data they collect from their customers to make better decisions on their marketing campaigns by gauging their experiences and attitudes around their use of and future vision for using customer data across multiple marketing channels. In order to understand this topic, we conducted interviews with 11 executives representing a range of roles and perspectives, including consumer packaged goods companies, financial services organizations, and agencies.
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acxiom, forrester, data, marketing, marketing campaigns, cross channel, customer data, market research, targeting, data analytics, life cycle management
    
Acxiom Corporation
Published By: Acxiom Corporation     Published Date: Mar 12, 2014
If you are responsible for online advertising, this report is going to change the way you look at your banner ads forever. It did for us. But, step one on the road to this transformation was deciding exactly what to measure. Download this whitepaper to learn about a new measurement approach that proves banner ads boost offline sales.
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acxiom, marketing, measurement, banner ads, display advertising, targeting, marketing campaigns, marketing analytics, data analytics, online engagement
    
Acxiom Corporation
Published By: SAS     Published Date: Apr 20, 2015
This report offers recommendations and best practices for implementing analytics in an organization. It provides in-depth analysis of current strategies and future trends for next-generation analytics.
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SAS
Published By: SAS     Published Date: Jul 14, 2015
With sophisticated analytics, government leaders can pinpoint the underlying value in all their data. They can bring it together in a unified fashion and see connections across agencies to better serve citizens.
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anayltics, data analysis, management, knowledge pooling, data infrastructure
    
SAS
Published By: SAS     Published Date: Oct 22, 2015
The Internet of Things (IoT) presents an opportunity to collect real-time information about every physical operation of a business. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors can deliver this information in real time. There is tremendous opportunity for those businesses that can convert raw IoT data into business insights, and the key to doing so lies within effective data analytics. To research the current state of IoT analytics, Blue Hill Research conducted deep qualitative interviews with three organizations that invested significant time and resources into their own IoT analytics initiatives. By distilling key themes and lessons learned from peer organizations, Blue Hill Research offers our analysis so that business decision makers can ultimately make informed investment decisions about the future of their IoT analytics projects.
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SAS
Published By: SAS     Published Date: Nov 04, 2015
In a panel discussion at the 12th annual SAS Health Analytics Executive Forum in May 2015, leaders from Dignity Health, Horizon Blue Cross Blue Shield of New Jersey, Janssen Pharmaceuticals and SAS shared what they have done to prove the value of analytics to their business leaders and what has worked for them as they developed an analytic culture in their organizations and put analytic insights to work.
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sas, healthcare, healthcare models, episode analytics, analytics, data management
    
SAS
Published By: SAS     Published Date: Nov 04, 2015
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in todays on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.
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data visualization, sas, big data, visual analytics, data exploration, analysis, networking, knowledge management, data management
    
SAS
Published By: SAS     Published Date: Nov 04, 2015
This paper is divided into two parts. The first part provides some background and a comparison of the types of episode analytics. Part two explores the real-world experiences of payers and providers in using episode analytics for payment bundling and other purposes. Finally, we offer some recommendations on how to use episode analytics to reduce variations and manage contracts that involve financial risk.
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sas, healthcare, healthcare models, episode analytics, payment bundling, data management, human resource technology
    
SAS
Published By: HPE     Published Date: Mar 23, 2015
With new technologies, new opportunities often emerge, especially in business. The advent of innovations, such as social media and mobile devices, is changing the ways businesses interact with customers and the ways in which customers desire to be engaged. Opportunities arising from the benefits of salesforce automation, business intelligence (BI), and customer relationship management (CRM) applications are providing new levels of insight, helping businesses acquire customers more efficiently and retain those customers longer. As a direct result, organizations that invest in better understanding potential customers are likely to see higher returns than those organizations that possess a more limited understanding of their customer base. Seeking the competitive advantage resulting from improved customer focus, IT organizations have increased investment in business intelligence and analytics and the underlying infrastructure to support those applications.
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HPE
Published By: RMS     Published Date: Jul 18, 2019
The more holistic view of risk a property underwriter can get, the better decisions they are likely to make. In order to build up a detailed picture of risk at an individual location, underwriters or agents at coverholders have, until now, had to request exposure analytics on single risks from their portfolio managers and brokers. Also, they had to gather supplementary risk data from a range of external resources, whether it is from Catastrophe Risk Evaluation and Standardizing Target Accumulations (CRESTA) zones to look-ups on Google Maps.
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RMS
Published By: RMS     Published Date: Jul 18, 2019
When evaluating single risks, underwriters and coverholders typically have to request exposure analytics from their portfolio managers and brokers, or gather their own supplementary risk data from a range of external resources, whether it is from Catastrophe Risk Evaluation and Standardizing Target Accumulations (CRESTA) zones, through to lookups on Google Maps. But all this takes valuable time, requires multiple user licenses and can generate information that is inconsistent with the underlying modeling data at the portfolio level.
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RMS
Published By: Caristix     Published Date: May 03, 2013
Diagnosoft selected Caristix software and consulting. Consulting work included a hands-on workshop to co-design the interface deployment workflows that Diagnosoft customer engagements would require.
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clinical analytics, interoperability, software, consulting, interface deployment, healthcare, medical, application integration, application performance management, best practices, business activity monitoring, business analytics, business integration, business intelligence, enterprise software
    
Caristix
Published By: Dell EMC     Published Date: May 10, 2017
While just about everyone is writing about how IT and the businesses it serves need to be transformed, the actual industry answers to both digital and IT transformation remain unclear at best. Are transformational initiatives all about analytics and big data? Or are they about the move to cloud in all its varieties? Support for mobile? More agile ways of working and developing software? Or are they actually all about crafting teams to promote more proactive dialog between the business and IT? The truth is, of course, digital and IT transformation depend on all of the above and more. They also depend on a resilient infrastructure thats easily adapted to changing business priorities without requiring long hours spent on maintenance, updates, and addressing problems of service availability. But making all this work clearly and cohesively is far beyond the purview of almost any solution todaywhether from a software management perspective or from a hardware infrastructure perspective.
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Dell EMC
Published By: FICO     Published Date: Aug 27, 2012
In this white paper, FICO describes how to use business rules management systems as a core technology to improve revenue while controlling costs.
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cost control, underwriting, insurance, pos, point of sale, revenue generation, analytics, decision management
    
FICO
Published By: SAP     Published Date: May 22, 2012
Is turning data into information still a challenge for your company? If so, you are not alone. View this on-demand Webinar with SAP and HP to learn how you can manage ever-increasing amounts of data; provide this data to business users to make critical decisions in a timely fashion; and enable true self-service business intelligence (BI) for business users.
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sap, business solutions, business technology, enterprise, technology, enterprise analytics, application integration, application performance management, best practices, business analytics
    
SAP
Published By: SAP     Published Date: May 22, 2012
Business intelligence technology must meet the demands of tomorrow's "digital natives"; integrate seamlessly with cloud data and platforms; alignpeople, conversations, and data with business strategy; and make the most of the infrastructures we have today.
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sap, business intelligence, business analytics, technology, application integration
    
SAP
Published By: Akamai Technologies     Published Date: Sep 11, 2017
Malicious botnets present multiple challenges to enterprises some threaten security, and others merely impact performance or web analytics. A growing concern in the bot environment is the practice of credential stuffing, which capitalizes on both a bots ability to automate repeat attempts and the growing number of online accounts held by a single user. As bot technologies have evolved, so have their methods of evading detection. This report explains how the credential stuffing exploit challenges typical bot management strategies, and calls for a more comprehensive approach.
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web analytics, frost & sullivan, bot management, botnet
    
Akamai Technologies
Published By: IBM APAC     Published Date: Jul 09, 2017
Organizations today collect a tremendous amount of data and are bolstering their analytics capabilities to generate new, data-driven insights from this expanding resource. To make the most of growing data volumes, they need to provide rapid access to data across the enterprise. At the same time, they need efficient and workable ways to store and manage data over the long term. A governed data lake approach offers an opportunity to manage these challenges. Download this white paper to find out more.
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data lake, big data, analytics
    
IBM APAC
Published By: Oracle EMEA     Published Date: Apr 15, 2019
Forward-thinking enterprises understand what it takes to be successful in this data-rich, increasingly automated economy. According to the Harvard Business Review Analytic Services research report The Rise of Intelligent Automation: TurningComplexity into Profit, sponsored by Oracle, at least 7 in 10 executives understand that predictive analytics (80%) and AI and machine learning (68%) are important for the future of the business. Even as executives recognize the vital role data plays in their businesses, many are unable to take advantage of the value residing in their data. The old ways of collecting, managing, storing, and analyzing data are no longer effective, and are preventing businesses from extracting potential value. Many simply cant execute on a data-driven vision.
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Oracle EMEA
Published By: Oracle EMEA     Published Date: Apr 15, 2019
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; its a whole new approach to getting more value from your data. Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results. Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployedeither on premises or in the cloudthey face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets. Oracle has a better way. Download this whitepaper to f
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Oracle EMEA
Published By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Todays organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.
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Amazon Web Services
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