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Published By: RMS     Published Date: Jul 25, 2019
U.S. Flood is a high-gradient, intricate peril incorporating various sources, and causing a variety of effects. It requires sophisticated models, data science, and analytics technology to properly understand and assess each risk.
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RMS
Published By: Google     Published Date: Aug 05, 2019
"Agile BI requires more than just agile dashboards. True agility means prototyping data models quickly so business users can continuously iterate on them. Application development and delivery professionals working on BI initiatives should consider adding DWA platforms to their BI toolbox. This Forrester report discusses how seven data warehouse automation vendors bring Agile options to all phases of BI/analytics application development. Read more to find out how these platforms help facilitate shorter development cycles."
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data warehouse automation, forrester, agile solutions, business intelligence, analytics
    
Google
Published By: Google     Published Date: Aug 05, 2019
As organizations continue to produce vast quantities of data, they increasingly need platforms that allow them to analyze, store, and extract meaningful insights from that data. Gartner helps data and analytics leaders evaluate 19 vendors in an increasingly split market. Download the Gartner Magic Quadrant report and find out more.
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data management, database solutions, databases, enterprise database, managed database
    
Google
Published By: Gigamon     Published Date: Sep 03, 2019
The IT pendulum is swinging to distributed computing environments, network perimeters are dissolving, and compute is being distributed across various parts of organizations’ infrastructure—including, at times, their extended ecosystem. As a result, organizations need to ensure the appropriate levels of visibility and security at these remote locations, without dramatically increasing staff or tools. They need to invest in solutions that can scale to provide increased coverage and visibility, but that also ensure efficient use of resources. By implementing a common distributed data services layer as part of a comprehensive security operations and analytics platform architecture (SOAPA) and network operations architecture, organizations can reduce costs, mitigate risks, and improve operational efficiency.
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Gigamon
Published By: KPMG     Published Date: Jun 10, 2019
Getting complex decisions right across complicated operational networks is the key to optimum performance. Find out how one of the UK’s biggest bus operators is using data and analytics to make better decisions and optimise the use of resources across their network. Read this story to discover: • how data and analytics can transform operational performance • the benefits of using decision-support tools in the middle office • key lessons for getting your plans for digital transformation right.
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KPMG
Published By: Cisco Umbrella EMEA     Published Date: Sep 02, 2019
"We live and surf in a cyber world where attacks like APT, DDOS, Trojans and Ransomware are common and easy to execute. Domain names are an integral part of any business today and apparently an integral part of an attacker's plan too. Domain names are carriers of malwares, they act as Command and Control servers and malware's ex-filtrate data too. In today's threat landscape - predicting threats, spotting threats and mitigating them is super crucial.. This is called Visibility and Analytics. Watch this on demand session with our Cisco cloud security experts Shyam Ramaswamy and Fernando Ferrari as they talk about how Cisco Umbrella and The Umbrella Research team detect anomalies, block threats and identify compromised hosts. The experts also discuss how effectively Cisco spot, react, filter out IOC, block the network communications of a malware; identify and stop a phishing campaign (unknown ones too). "
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Cisco Umbrella EMEA
Published By: TIBCO Software     Published Date: Feb 13, 2019
Analyst firms Gartner, Inc. and Forrester are projecting accelerated data virtualization adoption for both first-time and expanded deployments. What are the uses cases for this technology? At its Data and Analytics Summit in London in March 2018, Gartner answered this question by identifying 13 data virtualization use cases. This paper explores each of these use cases by: Identifying key requirements Showing how you can apply TIBCO® Data Virtualization to address these needs Listing the benefits you can expect when implementing TIBCO Data Virtualization for the use case
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
Digital business initiatives have expanded in scope and complexity as companies have increased the rate of digital innovation to capture new market opportunities. As applications built using fine-grained microservices and functions become pervasive, many companies are seeing the need to go beyond traditional API management to execute new architectural patterns and use cases. APIs are evolving both in the way they are structured and in how they are used, to not only securely expose data to partners, but to create ecosystems of internal and/or third-party developers. In this datasheet, learn how you can use TIBCO Cloud™ Mashery® to: Create an internal and external developer ecosystem Secure your data and scale distribution Optimize and manage microservices Expand your partner network Run analytics on your API performance
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
Tips and best practices for data analytics executives Organizations today understand the value to be derived from arguably their greatest asset—data. When successfully aggregated and analyzed, data can unlock valuable insights, solve problems, improve products and services, and help companies gain a competitive edge. However, analytics executives face significant challenges in collecting, validating and analyzing data to deliver the right analytic insight to the right person at the right time. This e-book is designed to help. First, we'll explore the growing expectations for data analytics and the rise of the analytics executive. Then we'll explore a range of specific challenges those executives face, including those around data blending, analytics, and the organization itself, and offer best practices and strategies for meeting them.
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
With the new TIBCO Spotfire® A(X) Experience, we are revolutionizing analytics and business intelligence. This new platform accelerates the personal and enterprise analytics experience so you can get from data to insights in the fastest possible way. With the fusion of technology enablers like machine learning, artificial intelligence, and natural language search, the Spotfire® X platform redefines what’s possible for analytics and business intelligence, simplifying for everyone how data and insights are generated, consumed, and acted on. Download this whitepaper to learn more, then check out the new Spotfire analytics. It’s unlike anything you have ever seen. Simple, yet powerful, it changes everything.
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
Analyst firms Gartner, Inc. and Forrester are projecting accelerated data virtualization adoption for both first-time and expanded deployments. What are the uses cases for this technology? At its Data and Analytics Summit in London in March 2018, Gartner answered this question by identifying 13 data virtualization use cases. This paper explores each of these use cases by: Identifying key requirements Showing how you can apply TIBCO® Data Virtualization to address these needs Listing the benefits you can expect when implementing TIBCO Data Virtualization for the use case
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
Digital business initiatives have expanded in scope and complexity as companies have increased the rate of digital innovation to capture new market opportunities. As applications built using fine-grained microservices and functions become pervasive, many companies are seeing the need to go beyond traditional API management to execute new architectural patterns and use cases. APIs are evolving both in the way they are structured and in how they are used, to not only securely expose data to partners, but to create ecosystems of internal and/or third-party developers. In this datasheet, learn how you can use TIBCO Cloud™ Mashery® to: Create an internal and external developer ecosystem Secure your data and scale distribution Optimize and manage microservices Expand your partner network Run analytics on your API performance
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
Tips and best practices for data analytics executives Organizations today understand the value to be derived from arguably their greatest asset—data. When successfully aggregated and analyzed, data can unlock valuable insights, solve problems, improve products and services, and help companies gain a competitive edge. However, analytics executives face significant challenges in collecting, validating and analyzing data to deliver the right analytic insight to the right person at the right time. This e-book is designed to help. First, we'll explore the growing expectations for data analytics and the rise of the analytics executive. Then we'll explore a range of specific challenges those executives face, including those around data blending, analytics, and the organization itself, and offer best practices and strategies for meeting them. We'll also provide a short overview of TIBCO Statistica, an easy-to-use predictive analytics software solution designed to turn big data into your bigg
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TIBCO Software
Published By: Group M_IBM Q3'19     Published Date: Sep 04, 2019
In the last few years we have seen a rapid evolution of data. The need to embrace the growing volume, velocity and variety of data from new technologies such as Artificial Intelligence (AI) and Internet of Things (IoT) has been accelerated. The ability to explore, store, and manage your data and therefore drive new levels of analytics and decision-making can make the difference between being an industry leader and being left behind by the competition. The solution you choose must be able to: • Harness exponential data growth as well as semistructured and unstructured data • Aggregate disparate data across your organization, whether on-premises or in the cloud • Support the analytics needs of your data scientists, line of business owners and developers • Minimize difficulties in developing and deploying even the most advanced analytics workloads • Provide the flexibility and elasticity of a cloud option but be housed in your data center for optimal security and compliance
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Group M_IBM Q3'19
Published By: Infinidat EMEA     Published Date: May 14, 2019
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
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Infinidat EMEA
Published By: Flexential     Published Date: Jul 17, 2019
In a data environment that’s become increasingly centralized by public cloud services, the “edge” is emerging as a critical solution for reducing latency for network-based services. Consumption habits of services and the need for analytics are shifting beyond core population centers, becoming local and even hyper-local within a region or city. As the online population continues to grow and new services emerge, the ability to handle data traffic securely – close to the customer or application – will become a common pattern for the new service evolution.
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Flexential
Published By: SAS     Published Date: Sep 05, 2019
Organizations are charging ahead with investments in cloud and analytics to deliver agility, scalability and cost savings. With computing power advancements and continuous growth of data, cloud provides the elastic workloads and flexibility required for modern business. However, the environment of flexibility and choice that cloud provides also creates complexity and challenges. In this white paper, learn how organizations are applying expertise and using the latest methods to move analytics to the cloud, including: • Why are organizations moving analytic work to the cloud? • What are the key challenges and misconceptions? • How do IT leaders provide choice while maintaining control?
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SAS
Published By: SAS     Published Date: Sep 05, 2019
Envision this situation at a growing bank. Its competitive landscape demands an agile response to evolving customer needs. Fortunately, analytically minded professionals in different divisions are seeing results that positively affect the bottom line. • A data scientist in the business development team analyzes data to create customized • experiences for premium customers. • A digital marketer tracks and influences the customer journey for prospective • mortgage customers. • A risk analyst builds risk models for the bank’s loan portfolios. • A data analyst examines data about local customers. • A technical architect defines a new system to protect bank data from internal and • external cyberthreats. • An application developer builds a new mobile app for online customer portfolio • management. Between them, these employees might be using more than a dozen packages for analytics and data management.
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SAS
Published By: MicroStrategy     Published Date: Aug 28, 2019
Over the last decade, the enterprise analytics landscape has dramatically transformed. Vendors have come and gone, and platforms have continually expanded their offerings to include new functionality and keep pace with the demands of the businesses they serve. Originally envisioned as an IT-centric tool for enterprise reporting, analytics today has evolved into a business solution—empowering a range of users across every line of business, including front-line employees, field personnel, and executives. The rise of self-service analytics over the past decade has played a key role in promoting a data-driven mindset within every business function. However, this practice is limited to a skilled few. The vast majority of business professionals lack the time, analytical skills, or inclination to conduct their own analyses, and fail to effectively use analytics on a day-to-day basis. The result? Despite decades of investments, BI adoption at most organizations remains at 30%. The failure of e
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MicroStrategy
Published By: MicroStrategy     Published Date: Aug 28, 2019
Why HyperIntelligence? Today, despite massive investments in data, IT infrastructure, and analytics software, the adoption of analytics continues to lag behind. In fact, according to Gartner, most organizations fail to hit the 30% mark. That means that more than 70% of people at most organizations are going without access to the critical information they need to perform to the best of their abilities. What’s stopping organizations from breaking through the 30% barrier and driving the pervasive adoption of intelligence? Simple. The majority of existing tools only cater to users who are naturally analytically inclined—the analysts, data scientists, and architects of the world. The other 70%—the people making the operational decisions daily within a business—simply lack the time, skill, or desire to seek out data and intelligence on their own. HyperIntelligence helps organizations operationalize their existing investments and arm everyone across the organization with intelligence. Whether
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MicroStrategy
Published By: MicroStrategy     Published Date: Aug 28, 2019
Data and analytics are the key accelerants of digitalization, transformation and “ContinuousNext” efforts. As a result, data and analytics leaders will be counted upon to affect corporate strategy and value, change management, business ethics, and execution performance.
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MicroStrategy
Published By: TIBCO Software     Published Date: Aug 20, 2019
TIBCO Data Virtualization is a proven approach used by four of the top five integrated energy companies to deliver more analytic data sooner from across upstream and downstream operations. Specific use cases described include: •? Offshore Platform Data Analytics •? Well Maintenance and Repair •? Cross Refinery Web Data Services •? SAP Master Data Quality If you are an energy company facing similar data and analytic challenges, consider TIBCO Data Virtualization.
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data virtualization, analytic data, oil&gas, improved roi, improved efficiency
    
TIBCO Software
Published By: Artemis Health     Published Date: Aug 08, 2019
Consultants and advisors are on the front lines of benefits data analytics. They’re the folks who dig through thousands of rows in a spreadsheet to surface problems and find solutions. In this whitepaper, we’ll dive deep on the advantages consultants offer to employers: • Access to data analytics, trend analysis, and program measurement • The expertise to identify, track, and take action on chronic conditions in a member population • The industry insight into public policy and regulation changes
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Artemis Health
Published By: Gigaom     Published Date: Oct 02, 2019
While interest in Machine Learning/Artificial Intelligence/ (ML/AI) has never been higher, the number of companies deploying it is only a subset, and successful implementations a smaller proportion still. The problem isn’t the technology; that part is working great. But the mere presence and provision of tools, algorithms, and frameworks aren’t enough. What’s missing is the attitude, appreciation, and approach necessary to drive adoption and working solutions. To learn more, join us for this free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and panelists Jen Stirrup, Lillian Pierson, and special guest from Cloudera Fast Forward Labs, Alice Albrecht. Our panel members are seasoned veterans in the database and analytics consulting world, each with a track record of successful implementations. They’ll explain how to go beyond the fascination phase of new technology towards the battened down methodologies necessary to build bulletproof solutions th
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Gigaom
Published By: SAS     Published Date: Jun 26, 2019
To support open government initiatives and uphold the values of transparency, participation and collaboration in the US, federal agencies today make their data open, or publicly accessible. Citizens can use this open data to assess college affordability, the economy, educational issues, environmental damage, health care, taxes, agriculture, the climate and more. Governments can use APIs to pull this open data into SAS Visual Analytics as a way to identify trends and patterns and obtain all sorts of new insights. With public health surveillance, for example, governments can monitor and evaluate indicators that point to high-risk areas so they’ll know where and how to focus efforts. Such public health surveillance can serve as an early warning system for impending emergencies, document the impact of an intervention, track progress toward public health goals, and clarify health problems to inform public health policies and strategies.
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SAS
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