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Published By: IBM     Published Date: Mar 30, 2017
To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize its value, and integrate it at a more granular level than ever before—focusing on the individual transaction level, rather than on general summary data. As data volumes continue to explode, clients must take advantage of a fully scalable information integration architecture that supports any type of data integration technique such as extract, transfer and load (ETL), data replication or data virtualization.
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data integration, data security, data optimization, data virtualization, database security
    
IBM
Published By: Datastax     Published Date: Aug 27, 2018
" For any business that wants to successfully compete in today’s digital economy, it is not a question of if but rather how much of their business will be done with cloud applications. A cloud application is one with many endpoints including browsers, mobile devices, and/or machines that are geographically distributed. The application is intensely transactional (high velocity reads and/or writes), always available, and instantaneously responsive no matter the number of users or machines using the application. Download this free white paper and explore how DataStax customers are delivering real-time value at epic scale with their cloud applications. Explore the core database requirements that make businesses successful with cloud applications, which include continuous availability, linear scale, and geographic distribution."
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Datastax
Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
After several years of relentless hardware and software innovation, the mainframe is at an inflection point. It’s quickly moving from being a supporting platform of transaction revenue to becoming a source of revenue growth and innovation. Organizations are evolving toward what IDC calls the “connected mainframe.” This evolution to the platform is also enabling the mainframe to play a central role in organizations’ digital transformation (DX) journey. Key steps in achieving the connected mainframe require that organizations modernize and integrate the platform with their internal and external environments. IDC finds that these modernization and integration initiatives lead to new business innovations, which in turn are driving revenue growth. Early adopters of a connected mainframe strategy have achieved more than 300% return on investment (ROI). Over 50% of the benefit value came from business productivity gains, realized from higher transaction volumes, new services, and/or business
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Group M_IBM Q418
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: Group M_IBM Q119     Published Date: Feb 25, 2019
The advantages blockchain can bring to the automotive ecosystem, both in facilitating collaboration among participants and enabling capabilities for new mobility business models, have gotten the attention of automotive executives. In addition to enabling a single source of data, blockchain can facilitate device-to-device transactions, smart contracts, and real-time processing and settlement. For the automotive industry, this translates into improvements and operational efficiencies in areas such as supply chain transparency, financial transactions between ecosystem participants, authenticating access to cars, and customer experience and loyalty.
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Group M_IBM Q119
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