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Results 1 - 25 of 85Sort Results By: Published Date | Title | Company Name
By: Gigamon     Published Date: Jun 10, 2019
Download “How to Strengthen Security While Optimizing Network Performance” to see how next-generation network packet brokers (NGNPBs) mitigate security tool sprawl, simplify IT management and improve network availability.  NGNPBs help align network and security teams by creating a single view of network infrastructure and data management. See why you should shift your infrastructure strategy toward NGNPBs to boost efficiency and reduce complexity. Learn more by downloading this new research now.
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Gigamon
By: Gigamon     Published Date: Mar 26, 2019
Download “How to Strengthen Security While Optimizing Network Performance” to see how next-generation network packet brokers (NGNPBs) mitigate security tool sprawl, simplify IT management and improve network availability. NGNPBs help align network and security teams by creating a single view of network infrastructure and data management. See why you should shift your infrastructure strategy toward NGNPBs to boost efficiency and reduce complexity. Learn more by downloading this new research now.
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Gigamon
By: Gigamon     Published Date: Feb 20, 2019
Download “How to Strengthen Security While Optimizing Network Performance” to see how next-generation network packet brokers (NGNPBs) mitigate security tool sprawl, simplify IT management and improve network availability. NGNPBs help align network and security teams by creating a single view of network infrastructure and data management. See why you should shift your infrastructure strategy toward NGNPBs to boost efficiency and reduce complexity. Learn more by downloading this new research now.
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Gigamon
By: Workday     Published Date: Feb 04, 2019
"Read now to learn about three key steps drawn from the “2018 Deloitte Global Human Capital Trends” report that emerging organisations can take to attract and retain top talent, including: ? Redefining careers ? Creating more personalised performance enablement to boost employee engagement ? Using data-driven technology and analytics to enhance business value "
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workday, workforce technology, digital strategy
    
Workday
By: Workday UK     Published Date: Jan 31, 2019
Read now to learn about three key steps drawn from the “2018 Deloitte Global Human Capital Trends” report that emerging organisations can take to attract and retain top talent, including: Redefining careers Creating more personalised performance enablement to boost employee engagement Using data-driven technology and analytics to enhance business value
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workday, workforce technology, digital strategy
    
Workday UK
By: Gigamon     Published Date: Dec 13, 2018
Perimeter-based solutions for network security do not work, leading to tool sprawl and performance issues. Read CSO Magazine’s interview with Gigamon CISO, Simon Gibson, to learn why a new, more intelligent approach is needed to build resilience into technology operations. “Security Should Be an Enabler” talks about an architectural approach that distributes only relevant data to appropriate tools, enabling an adaptable, simplified model at a reduced cost. Read now.
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Gigamon
By: Gigamon     Published Date: Dec 13, 2018
Read “How to Strengthen Security While Optimizing Network Performance” to see how next-generation network packet brokers (NGNPBs) mitigate security tool sprawl, simplify IT management and improve network availability. NGNPBs help align network and security teams by creating a single view of network infrastructure and data management. See why you should shift your infrastructure strategy toward NGNPBs to boost efficiency and reduce complexity. Learn more by reading this new research now.
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Gigamon
By: CyberSource     Published Date: Oct 19, 2018
Did you know that hackers aren’t just interested in large enterprise businesses? Or that you can operate your business without raw payment data? Learn the truth about the five most common payment security myths today in this informative e-book.
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CyberSource
By: HERE Technologies     Published Date: Sep 26, 2018
Mobile has become the first screen for consumers in terms of internet time spent. Hyperlocal location data is unique to mobile and provides a lot of new, valuable information about consumers. Today’s sophisticated buyers demand more transparency in location data science, better campaign performance and ROI from attribution modeling. Finding the right partner that can help build the bridge between real-world consumer behavior and mobile programmatic advertising in a transparent way is essential. To meet those challenges and address the demand for top quality location data, adsquare integrated a global database of HERE Places in April 2017. By leveraging HERE Places and overlaying raw location data of anonymous users with POI data points, adsquare is able to understand exactly what consumers are doing in the real world: what places they visit, when and how often. To find out more download this paper today.
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HERE Technologies
By: SAS     Published Date: Aug 28, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
By: SAS     Published Date: Aug 28, 2018
“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
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SAS
By: Engagio     Published Date: Jun 26, 2018
This is an inside look at the state of Account Based Marketing. More specifically, our research examined: ?How companies are utilizing ABM as a strategy ?How organizations are structuring their teams to support ABM ?How ABM can be measured at different stages ?The challenges most organizations are facing regarding ABM Along with showing the results, we’ve included our interpretation of the data to help you draw insights and apply them as you continue down your ABM journey. The research underscores where companies are at with their ABM programs and the key challenges they are facing. Regardless of your company size or maturity, there is always a need to grow your business and drive efficiency. The data from this survey illustrates how ABM can help.
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Engagio
By: Adverity     Published Date: Jun 15, 2018
A Beginner's Guide to Marketing Data Analytics Marketing Data is big & highly fragmented Big data is messy. It’s scattered across platforms, it’s diverse, and in its raw form, it’s practically unusable. We know, it’s a painful truth. The fact of the matter is that having a lot of data doesn’t necessarily mean that you have the answers to your most pressing questions. Looking for the most relevant bits in your pile of big data is like looking for a needle in a haystack. But don't you worry - we are here to help. This handy e-book will give you a short overview what quality matters, why data is so important and what you need to pay attention to. Best thing is: getting this ebook is super easy. Just fill out the form to the right and voilá - your download is ready. Enjoy this read!
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marketing business intelligence, saas marketing optimization, measuring marketing performance, roi analytics, automated report generator, performance based marketing, online marketing data, roi metrics, marketing reports, roi reporting, reporting generator, automated reporting tool, marketing dashboard, marketing data, marketing intelligence, report software, marketing reporting, marketing metrics, performance marketing, marketing performance
    
Adverity
By: CyberSource     Published Date: Apr 25, 2018
Did you know that hackers aren’t just interested in large enterprise businesses? Or that you can operate your business without raw payment data? Learn the truth about the five most common payment security myths today in this informative e-book.
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CyberSource
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
By: Carbon Black     Published Date: Apr 10, 2018
For decades, the financial services industry has endured constant change and uncertainty, from the depths of a financial crisis to widespread regulation overhauls. With the advent of more advanced cybersecurity threats, the industry has responded with rapid digital transformation to remain competitive while also pushing the envelope. Today, managing and mitigating cyber-related risks not only draws government scrutiny, but increased consumer scrutiny as well, with longstanding brand reputations anchored to institutions’ ability to protect its most sensitive data. In a recent survey of Americans, financial information was considered by consumers to be their most valuable personal information, worth even more than personal or family photos and videos. For consumers, failing to protect their data is a grave violation of trust, to the point where 72% would consider leaving their current financial institution if their sensitive information was taken hostage by ransomware.1 Not only does the
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Carbon Black
By: SAS     Published Date: Mar 06, 2018
Known for its industry-leading analytics, data management and business intelligence solutions, SAS is focused on helping organizations use data and analytics to make better decisions, faster. The combination of self-service BI and analytics positions you for improved productivity and smarter business decisions. So you can become more competitive as you use all your data to take better actions. Instead of depending on hunch-based choices, you can make decisions that are truly rooted in discovery and analytics. And you can do it through an interface that anyone can use. At last, your business users can get close enough to the data to manipulate it and draw their own reliable, fact-based conclusions. And they can do it in seconds or minutes, not hours or days. Equally important, IT remains in control of data access and security by providing trusted data sets and defined processes that promote the valuable, user-generated content for reuse and consistency. But, they are no longer forced
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SAS
By: SAS     Published Date: Mar 06, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
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SAS
By: Snowflake     Published Date: Jan 25, 2018
"The forces that gave rise to data warehousing in the 1980s are just as important today. However, history reveals the benefits and drawbacks of the traditional data warehouse and how it falls short. This eBook explains how data warehousing has been re-thought and reborn in the cloud for the modern, data-driven organization."
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Snowflake
By: SAS     Published Date: Jan 17, 2018
The Industrial Internet of Things (IIoT) is flooding today’s industrial sector with data. Information is streaming in from many sources — equipment on production lines, sensors at customer facilities, sales data, and much more. Harvesting insights means filtering out the noise to arrive at actionable intelligence. This report shows how to craft a strategy to gain a competitive edge. It explains how to evaluate IIoT solutions, including what to look for in end-to-end analytics solutions. Finally, it shows how SAS has combined its analytics expertise with Intel’s leadership in IIoT information architecture to create solutions that turn raw data into valuable insights.
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SAS
By: Pure Storage     Published Date: Jan 12, 2018
Interest in machine learning has exploded over the past decade. You see machine learning in computer science programs, industry conferences, and the Wall Street Journal almost daily. For all the talk about machine learning, many conflate what it can do with what they wish it could do. Fundamentally, machine learning is using algorithms to extract information from raw data and represent it in some type of model. We use this model to infer things about other data we have not yet modeled. Neural networks are one type of model for machine learning; they have been around
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learning machines, automated intelligence, scalars, vectors, mathematics, classification, pure storage
    
Pure Storage
By: OracleSMB     Published Date: Jan 04, 2018
Finance has grown beyond recording and reporting. Leaders in fast-growing companies need not only the raw financial data, but the sophisticated analysis to make sense of it all. In today’s digital world, Finance must move out of the back-office and help drive the direction of the business, as well as improve the bottom line through more efficient processes and increased responsiveness. With the right tools, your finance team can simplify processes and fulfill its goal of adding value.
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OracleSMB
By: Pure Storage     Published Date: Nov 02, 2017
To stay relevant in today’s competitive, digitally disruptive market, and to stay ahead of your competition, you have to do more than just store, extract, and analyze your data — you have to draw the true business value out of it. Fail to evolve, and your organization might be left behind as companies ramp up and speed up their competitive, decision-making environments. This means deploying cost-effective, energy-efficient solutions that allow you to quickly mine and analyze your data for valuable information, patterns, and trends, which in turn can enable you to make faster ad-hoc decisions, reduce risk, and drive innovation.
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storage solutions, pure storage, oracle, analytics, business value, innovation, risk reduction
    
Pure Storage
By: Hewlett Packard Enterprise     Published Date: Oct 23, 2017
Midsized firms operate in the same hypercompetitive, digital environment as large enterprises—but with fewer technical and budget resources to draw from. That’s why it is essential for IT leaders to leverage best-practice processes and models that can help them support strategic business goals such as agility, innovation, speed-tomarket, and always-on business operations. A hybrid IT implementation can provide the infrastructure flexibility to support the next generation of high-performance, data-intensive applications. A hybrid foundation can also facilitate new, collaborative processes that bring together IT and business stakeholders.
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digital environment, hyper competitive, business goals, hybrid it, technology, hpe
    
Hewlett Packard Enterprise
By: SAS     Published Date: Oct 18, 2017
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
Tags : 
    
SAS
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