data analytics

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Published By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
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aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state
    
Aberdeen
Published By: IBM     Published Date: May 02, 2017
An interactive white paper describing how to get smart about insider threat prevention - including how to guard against privileged user breaches, stop data breaches before they take hold, and take advantage of global threat intelligence and third-party collaboration. Security breaches are all over the news, and it can be easy to think that all the enemies are outside your organization. But the harsh reality is that more than half of all attacks are caused by either malicious insiders or inadvertent actors.1 In other words, the attacks are instigated by people you’d be likely to trust. And the threats can result in significant financial or reputational losses.
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insider threats, data management, organization management, data analytics, threat detection, risk management, fraud discovery, forensics investigation
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
The data integration tool market was worth approximately $2.8 billion in constant currency at the end of 2015, an increase of 10.5% from the end of 2014. The discipline of data integration comprises the practices, architectural techniques and tools that ingest, transform, combine and provision data across the spectrum of information types in the enterprise and beyond — to meet the data consumption requirements of all applications and business processes. The biggest changes in the market from 2015 are the increased demand for data virtualization, the growing use of data integration tools to combine "data lakes" with existing integration solutions, and the overall expectation that data integration will become cloud- and on-premises-agnostic.
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data integration, data security, data optimization, data virtualization, database security, data analytics, data innovation
    
IBM
Published By: IBM     Published Date: May 23, 2017
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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cloud strategy, database projects, disaster recover, geographic reach, large database, ibm, analytics, management optimization
    
IBM
Published By: Viavi Solutions     Published Date: Apr 14, 2017
In the age of information, staying on top of emerging threats requires IT teams to leverage existing tools in innovative ways, such as applying deep packet inspection and analysis from performance monitoring solutions for advanced security forensics. Based on recent insight gathered from 322 network engineers, IT directors and CIOs around the world, 85 percent of enterprise network teams are now involved with security investigations, indicating a major shift in the role of those teams within enterprises. Large-scale and high-profile security breaches have become more common as company data establishes itself as a valuable commodity on the black market. As such, enterprises are now dedicating more IT resources than ever before to protect data integrity.
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network security, security validation, technical security, cyber attacks, database security, it security, traffic analytics, data report
    
Viavi Solutions
Published By: SAS     Published Date: Apr 25, 2017
Physicians and their patients, medical policy makers and licensing boards, pharmaceutical companies and pharmacies all must work together to stem the opioid epidemic and achieve the fundamental objectives of reducing addiction and deaths. With so many players and data sources, today’s information is partial, fragmented, and often not actionable. We don’t have the data to understand what’s happening, to adjust policy, and to motivate physicians and patients to change their behaviors. Better data and analytics can help develop better treatment protocols, both for pain in the first place and for remediation when patients are becoming dependent on the drugs.
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SAS
Published By: SAS     Published Date: Apr 25, 2017
Insurers have long been plagued by fraud, error, waste, and abuse in health care payments. The costs are huge – amounting to as much as 25 percent of payments made. Today’s data management and analytics platforms promise breakthroughs by incorporating comparative and behavioral data to predict as well as detect loss in all its forms. To explore the opportunities and how insurers can capitalize on them, IIA spoke with Ben Wright, Sr. Solutions Architect in SAS’s Security Intelligence Global Practice.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
From cars to factories to cities, many governments are already collecting information from citizens and connected devices that send and receive data over the internet of things (IoT). While analysts expect the IoT to soar to tens of billions of devices by 2020, no one knows how many or what new types of intelligent devices will emerge. But we do know that traditional approaches to data management and analytics may not be sufficient for sustaining value in this new, connected world
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SAS
Published By: IBM     Published Date: Apr 03, 2017
Businesses today certainly do not suffer from a lack of data. Every day, they capture and consume massive amounts of information that they use to make strategic and tactical decisions. Yet organizations often lack two critical capabilities when it comes to making the right decisions for the business: the ability to make accurate predictions about the future, and to then use those predicted insights in conjunction with organizational goals to identify the best possible actions they should take. The combination of predictive analytics and decision optimization provides organizations with the ability to turn insight into action. Predictive analytics offers insights into likely scenarios by analyzing trends, patterns and relationships in data. Decision optimization prescribes best-action recommendations given an organization’s business goals and business dynamics, taking into account any tradeoffs or consequences associated with those actions.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources, data optimization
    
IBM
Published By: IBM     Published Date: Apr 03, 2017
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins. Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses. Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources
    
IBM
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
    
IBM
Published By: IBM     Published Date: Apr 20, 2017
An interactive white paper describing how to get smart about insider threat prevention - including how to guard against privileged user breaches, stop data breaches before they take hold, and take advantage of global threat intelligence and third-party collaboration. Security breaches are all over the news, and it can be easy to think that all the enemies are outside your organization. But the harsh reality is that more than half of all attacks are caused by either malicious insiders or inadvertent actors.1 In other words, the attacks are instigated by people you’d be likely to trust. And the threats can result in significant financial or reputational losses.
Tags : 
insider threats, data management, organization management, data analytics, threat detection, risk management, fraud discovery, forensics investigation
    
IBM
Published By: IBM     Published Date: May 01, 2017
If you function like most IT organizations, you've spent the past few years relying on mobile device management (MDM), enterprise mobility management (EMM) and client management tools to get the most out of your enterprise endpoints while limiting the onset of threats you may encounter. In peeling back the onion, you'll find little difference between these conventional tools and strategies in comparison to those that Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs) have employed since the dawn of the modern computing era. Their use has simply become more: Time consuming, with IT trudging through mountains of endpoint data; Inefficient, with limited resources and limitless issues to sort through for opportunities and threats; and Costly, with point solution investments required to address gaps in OS support across available tools. Download this whitepaper to learn how to take advantage of the insights afforded by big data and analytics thereby usher i
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ibm, endpoint management, mobile device management, enterprise mobility, os support, it organizations
    
IBM
Published By: IBM     Published Date: Jun 21, 2017
There are many types of databases and data analysis tools to choose from when building your application. Should you use a relational database? How about a key-value store? Maybe a document database? Is a graph database the right ft? What about polyglot persistence and the need for advanced analytics? If you feel a bit overwhelmed, don’t worry. This guide lays out the various database options and analytic solutions available to meet your app’s unique needs. You’ll see how data can move across databases and development languages, so you can work in your favorite environment without the friction and productivity loss of the past.
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data analysis, key value, document database, analytics
    
IBM
Published By: IBM     Published Date: Jun 21, 2017
NoSQL databases and Apache Spark are a potent combination for rapid integration, transformation and analysis of all kinds of business data. With its data syncing and analytics capabilities, IBM Cloudant offers unique advantages as a NoSQL database for many Spark use cases. IT decision-makers, data scientists and developers need to know how and when to apply these technologies most effectively. IBM can offer a host of resources and tools to help your organization gain value from Cloudant and Spark quickly, and with minimal up-front investment.
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ibm, ibm cloudant, apache spark, nosql, database
    
IBM
Published By: SAS     Published Date: Apr 20, 2017
Enterprises routinely claim to be focused on the customer experience, yet few really keep that promise. What’s in the way? Fragmentation and complexity in both customer data and customer-facing processes. IIA spoke with Wilson Raj, Global Director of Customer Intelligence, and Jonathan Moran, Customer Intelligence Product Marketing at SAS Institute Inc. about how organizations can leverage technology platforms and analytics to become more completely and genuinely customer-centric – making connections in the right way, at the right time, and on the right device.
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SAS
Published By: SAS     Published Date: Apr 20, 2017
With more data in the hands of more people – and easier access to easy-to-use analytics – conversations about data and results from data analysis are happening more often. And becoming more important. And expected. So it’s not surprising that improved collaboration is one of the most common organizational goals. Let’s take a look at how you can use results produced by SAS Visual Analytics with Microsoft Office applications. You’ll see how easy it is to combine sophisticated analytic visualizations and reports with Microsoft’s widely used productivity tools – to share insights, improve collaboration and drive increased adoption of analytics and BI across your organization.
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SAS
Published By: SAS     Published Date: Apr 25, 2017
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 today’s 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. The heart and soul of SAS Visual Analytics is the SAS® LASR™ Analytic Server, which ca
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SAS
Published By: SAS     Published Date: Apr 25, 2017
Are you a marketing leader on the path to modernizing your marketing organization? Are you a marketing analyst championing analytical transformation in your campaigns? If you answered yes to either question, this e-book is for you. It offers a practical account of how to create a new marketing culture that adds value through data and analytics. You’ll meet marketing leaders from Comerica, Lenovo, RCI, SAS and Visa – and read how they’re implementing analytics, redefining marketing strategies and transforming their cultures. By sharing their perspectives, we hope to provide a new set of best practices to guide your analytical transformation – and to help you reinvent your marketing organization for the digital age.
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SAS
Published By: Mindfire     Published Date: May 07, 2010
In this report, results from well over 650 real-life cross-media marketing campaigns across 27 vertical markets are analyzed and compared to industry benchmarks for response rates of static direct mail campaigns, to provide a solid base of actual performance data and information.
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mindfire, response rates, personalized cross-media, marketing campaign, personalization, personalized urls, purls, performance data
    
Mindfire
Published By: SAP     Published Date: May 18, 2014
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
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