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Results 1 - 25 of 73Sort Results By: Published Date | Title | Company Name
By: Group M_IBM Q3'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
By: Group M_IBM Q3'19     Published Date: Sep 04, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
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
By: Infinidat EMEA     Published Date: May 14, 2019
Data is the DNA of modern healthcare. As healthcare technology continues to evolve at a rapid pace, and patient data management and security evolve, emerging approaches for disease treatment and prevention—like precision medicine and healthcare content management—are becoming more necessary. Precision medicine is about moving from generic to more precise, population-focused diagnostics and treatment by factoring in data from patients’ genes, environment, lifestyle factors and family history, into clinical decision-making for earlier, more accurate diagnoses, and more effective treatment and prevention. Data is at the heart of enabling doctors and scientists to execute on this mission. Additionally, rapidly changing regulations throughout the world are affecting the management of all healthcare data. Infinidat removes data management barriers from this level of data interaction by removing isolated islands of storage and allowing much more data to reside on a single, high-performance, h
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Infinidat EMEA
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
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
By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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Cisco
By: HERE Technologies     Published Date: Mar 11, 2019
Increasingly sophisticated location technology makes it possible for data scientists to gain a deeper understanding of their target audiences – and how to reach them. Accurate and precise intelligence can give more timely and complete insights into audiences than ever before. As one of the world’s leading location platforms in 2018, HERE shares insights and solutions to buying location data for better audience segmentation.
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location data, ad tech, location targeting
    
HERE Technologies
By: SmartLink Health     Published Date: Oct 25, 2018
Payer contracts, relationships, and a strong service portfolio give your lab a license to hunt and an opportunity to compete. But lack of EHR integration continues to be a barrier for independent labs and a differentiator for the largest lab companies. In this webinar, you’ll discover a new, affordable, and innovative lab-to-EHR integration approach that eliminates the need for HL-7 interfaces and can help you: • Reduce incomplete lab orders and associated labor costs • Improve customer satisfaction and “stickiness” in your accounts • Grow both new and existing customer revenue
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SmartLink Health
By: IBM APAC     Published Date: Mar 06, 2019
The Forrester Study on cost savings and business benefits enabled by Watson Studio and Watson Knowledge Catalog. Watson Studio provides a suite of tools for data scientists, application developers, and subject matter experts to collaboratively and easily work with data and use that data to build, train and deploy machine learning models at scale. The Forrester provides readers a framework to evaluate the potential financial impact of the Watson Studio and Watson Knowledge Catalog investment on their organizations.
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IBM APAC
By: Intel     Published Date: Jun 07, 2017
Intel's Bob Rogers, chief data scientist for big data solutions, sat down with Dan Magestro, research director at the international Institute of Analytics (IIA), to discuss the power of asking questions when assessing an organisation's analytics maturity. Read on to find out more.
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intel, analytics, data, data analytics, data science
    
Intel
By: Teradata     Published Date: Oct 15, 2012
Does your organization struggle to get new business insights from all data types with rapid exploration?
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data scientists, analyst, statistician, quants, quantitative analyst, scientist, data science
    
Teradata
By: Virgin Pulse     Published Date: Jun 02, 2017
This report includes analysis from behavior and data scientists to help you understand why your employees may not be working at optimal levels and discover ways to address this growing problem.
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presenteeism, employee presenteeism, workforce presenteeism, job presenteeism, presenteeism in the workplace, worker productivity, workforce productivity
    
Virgin Pulse
By: TIBCO Software     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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TIBCO Software
By: HP Inc.     Published Date: Jun 12, 2018
HP scientists had a bright idea. If they could modify materials to absorb infrared light – the light we can’t see – they could successfully fuse color to that material. It’s a story of how HP “cracked the code” in 3D color printing by drawing upon deep experience in the science of ink. Read this innovation story to why HP Jet Fusion 300/500 3D printers make it possible to produce engineering-grade functional parts faster and more affordably. Download HP’s innovation story
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HP Inc.
By: SAS     Published Date: Apr 20, 2015
To create real business value with data scientists, top management must learn how to manage them effectively.
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SAS
By: EMC Corporation     Published Date: Jul 07, 2013
3TIER helps organizations understand and manage the risks associated with renewable energy projects. A pioneer in wind and solar generation risks analysis, 3TIER uses science and technology to frame the risk of weather-driven variability, anywhere on Earth. 3TIER's unique expertise is in combining the latest weather data with historical weather patterns, and using the expertise of 3TIER's meteorologists, engineers and data scientists to create a detailed independent assessment of the future renewable energy potential of any location.
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renewable energy, customer profile, emc, risk management, best practices, storage, technology, security
    
EMC Corporation
By: HP Inc.     Published Date: Apr 11, 2018
HP scientists had a bright idea. If they could modify materials to absorb infrared light – the light we can’t see – they could successfully fuse color to that material. It’s a story of how HP “cracked the code” in 3D color printing by drawing upon deep experience in the science of ink. Read this innovation story to why HP Jet Fusion 300/500 3D printers make it possible to produce engineering-grade functional parts faster and more affordably. Download HP’s innovation story
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HP Inc.
By: Veritas     Published Date: Oct 03, 2016
This benchmark report, the Data Genomics Index, encompasses a community of like-minded data scientists, industry experts, and thought leaders together with the purpose of better understanding the true nature of the unstructured data that we are creating, storing, and managing on a daily basis - a report on real storage environments’ composition.
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Veritas
By: IBM     Published Date: Jul 14, 2016
This video describes how data scientists, analysts and business users can save precious time by using a combination of SPSS and Spark to uncover and act on insights in big data.
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ibm, data, analytics, predictive business, ibm spss, apache spark, coding, data science
    
IBM
By: Oracle     Published Date: Mar 01, 2019
To keep up with rapid growth and stay ahead, disruptor fintechs must stay agile and go on innovating. Bangkok-based Forth Smart provides payment gateways that turn cash into digital currency via its thousands of vending machines. They needed to approach ITin new ways in order to free up budgets, resources and imaginations to focus on innovation. Oracle Cloud Specialist Marek Winiarski, talked to Forth Smart’s Data Scientist, Pawarit ‘Taa’ Ruengsuksilp about how the company has made cost savings and improved customer experience by adopting Oracle Autonomous Data Warehouse.
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Oracle
By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. The biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation. The increasing volume, variety, and velocity of data is putting pressure on organizations to rethink traditional methods of preparing data for reporting, analysis, and sharing. Download this white paper to find out how you can improve your data preparation for business analytics.
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Waterline Data & Research Partners
By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. To perform data discovery and exploration, use analytics to define desired business outcomes, and derive insights to help attain those outcomes, users need good, relevant data. Executives, managers, and other professionals are reaching for self-service technologies so they can be less reliant on IT and move into advanced analytics formerly limited to data scientists and statisticians. However, the biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation.
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Waterline Data & Research Partners
By: IBM     Published Date: Oct 21, 2016
Between the Internet of Things, customer experience and loyalty programs, social network monitoring, connected enterprise systems and other information sources, today's organizations have access to more data than they ever had before-and frankly, more than they may know what to do with. The challenge is to not just understand that data, but actualize it and use it to recognize real business value. This ebook will walk you through a sample scenario with Albert, a data scientist who wants to put text analytics to work by using the Word2vec algorithm and other data science tools.
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ibm, analytics, aps, aps data, open data science, data science, word2vec, enterprise applications
    
IBM
By: Veritas     Published Date: May 12, 2016
The Data Genomics Index is a first-of-its-kind benchmark analysis of data stored within a typical enterprise environment. This report reveals insights into data growth, data age, and data type thereby providing organizations with the comparison standard for beginning to take action on their data. In addition to the Index, Veritas has founded the Data Genomics Project. This community of likeminded data scientists, industry experts and thought leaders will come together to surface the true nature of enterprise environments, build the data-genome that matters for information management, and share the discussion with a world struggling to solve tremendous data growth challenges.
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Veritas
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