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Published By: Group M_IBM Q2'19     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 Q2'19
Published 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
Published By: Oracle     Published Date: Jun 10, 2019
Data is central to marketing function, yet research shows that 50% of CMOs struggle to manage data volumes, or gain insights. Read how to address data ethics and management in your organisation. Marketing’s top priority is to enforce technologies enabling real time data insights to drive instant, personalised CX. Meanwhile, only 30% of CMOs say they have data visualisation dashboards to analyse specific sets of data. Read the findings
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Oracle
Published By: Oracle     Published Date: Jun 04, 2019
Data is central to marketing function, yet research shows that 50% of CMOs struggle to manage data volumes, or gain insights. Read how to address data ethics and management in your organisation. Marketing’s top priority is to enforce technologies enabling real time data insights to drive instant, personalised CX. Meanwhile, only 30% of CMOs say they have data visualisation dashboards to analyse specific sets of data. Read the findings
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Oracle
Published By: HERE Technologies     Published Date: Dec 05, 2018
Car data consumption is critically important to auto manufacturers. As more vehicles are produced with built-in infotainment systems, the cost of supplying them with live information and real-time updates via a data connection grows ever greater. Auto manufacturers need to be able to enhance the driving experience with smart traffic, navigation, and entertainment services, while reducing costs and data volumes. HERE is the world’s leading provider of traffic data to the automotive industry. This eBook shows how HERE optimizes traffic solutions and it outlines how data use modelling, standardization, and good data management can help reduce usage.
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traffic data, auto, location data
    
HERE Technologies
Published By: AWS     Published Date: Nov 28, 2018
Financial institutions run on data: collecting it, analyzing it, delivering meaningful insights, and taking action in real time. As data volumes increase, organizations demand a scalable analytics platform that can meet the needs of data scientists and business users alike. However, managing an on-premises analytics environment for a large and diverse user base can become time-consuming, costly, and unwieldy. Tableau Server on Amazon Web Services (AWS) is helping major Financial Services organizations shift data visualization and analytics workloads to the cloud. The result is fewer hours spent on manual work and more time to ask deeper questions and launch new data analyses, with easily-scalable support for large numbers of users. In this webinar, you’ll hear how one major asset management company made the shift to cloud data visualization with Tableau Server on AWS. Discover lessons learned, best practices tailored to Financial Services organizations, and starting tactics for scalable analytics on the cloud.
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AWS
Published By: AWS     Published Date: Oct 26, 2018
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? Since data—structured and unstructured—can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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data, lake, amazon, web, services, aws
    
AWS
Published By: TIBCO Software     Published Date: Aug 13, 2018
The combination of legislation, market dynamics, and increasingly sophisticated risk management strategies requires you to be proactive in detecting risks like fraud quicker and more effectively. Dynamic detection systems need to adapt to evolving compliance regulations, scale to deal with growing transaction volumes, detect sophisticated risk specific patterns, and reduce false-positives. TIBCO's Risk Management Accelerator uses a combination of predictive analytics, streaming analytics, and business process management to deliver a powerful and cost-effective system for detecting anomalies. Download this solution brief to learn more.
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TIBCO Software
Published By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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Amazon Web Services
Published By: Redstor UK     Published Date: May 02, 2018
Many organisations are facing challenges relating to the unstructured data they hold. By its very nature, unstructured data is in a form that is difficult to manage, and it is growing rapidly in size. This can make it difficult to understand who owns that data, whether it is being used or even whether it is of any value. Industry forecasts indicate the volume of data generated by corporates is expected to double over the next three years and, with General Data Protection Regulation taking effect in May 2018, organisations need a more efficient way to manage and control this data. This White Paper provides an overview of the important technical considerations senior business and IT management teams need to review before choosing an archiving provider.
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Redstor UK
Published By: Thomson Reuters     Published Date: Mar 08, 2018
Many seasoned attorneys will agree that remediating an enormous amount of documentation to ensure regulatory compliance is no easy feat. The volume of repapering necessary for compliance with the new rules governing margin requirements for non-centrally cleared derivatives (UMR) presented new challenges, exposed structural weaknesses, and provided many lessons learned which can be applied to any documentation remediation effort. Many UMR initiatives suffered significant hurdles that contributed to delays and missed deadlines. Common among the various challenges faced were the dearth of talent in the quantities needed, and the limited technology and data management solutions utilized.
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legal. umr, project, management, alsp, thomson, reuters
    
Thomson Reuters
Published By: SAS     Published Date: Mar 06, 2018
As your organization struggles with growing volumes and sources of data, increasingly complex regulatory requirements, and pressure to do more with fewer resources, SAS Data Management can help. How? Our solution helps you make sense of your data so you can make better decisions. Then you can take the right actions to improve customer experience, boost revenue, become more efficient and remain compliant
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SAS
Published By: Gemini Data     Published Date: Jan 16, 2018
The increasing reliance on big data platforms for all functions of the organization has been transformative. As these environments mature and data volumes increase, organizations face infrastructure and management scalability challenges. Gemini Enterprise Manager simplifies deployment and management with a turnkey, NoOps appliance, providing simplicity, security, and speed to accelerate the time to value for any analysis use case. Manager allows you to control your Splunk deployment as a single, unified solution deployed on premises, in the cloud or both.
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Gemini Data
Published By: Group M_IBM Q1'18     Published Date: Dec 21, 2017
Consider the volume of business content that your organization generates or receives every day: applications, forms, reports, office documents, audio, video, and even social media about your company. If it is poorly managed, not digitized, or disconnected from critical business processes, it creates chaos. This chaos impacts your ability to deliver exceptional customer service; it slows down important processes, increases security risk, and negatively impacts revenue. Conversely, controlling content chaos can significantly improve your analytics strategy by gaining insight and business value from dark or unstructured data sources. In this eBook, learn how cognitive and cloud-based Enterprise Content Management, or ECM, can help you protect your content while gaining a competitive advantage from it as you grow.
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business content, volume, cloud-based, enterprise content management, ecm
    
Group M_IBM Q1'18
Published By: Zebra ABM     Published Date: Dec 14, 2017
Meet the demands of your highest-volume POS lanes with Zebra MP7000 next generation multi-plane 1D/2D imager. The MP7000 is loaded with features that take scanning performance and simplicity to the next level, enabling faster-than-ever checkout in cashier-manned and self-checkout lanes, improving cashier productivity, POS throughput and the shopper experience. A smart investment, the MP7000 offers an unmatched industry-best total cost of ownership (TCO) by delivering maximum uptime and minimum power consumption in an easy-to-service design with fewer parts and components. And with Zebra's complimentary powerful management applications, you can remotely manage all of your MP7000s, no matter where they are located.
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scanner, customer, productivity, mp7000, tco, total cost of ownership
    
Zebra ABM
Published By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
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population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
    
IBM Watson Health
Published By: AWS     Published Date: Nov 02, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it’s readily available to be categorized, processed, analyzed, and consumed by diverse groups within an organization. Since data - structured and unstructured - can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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AWS
Published By: Amazon Web Services     Published Date: Oct 09, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyse data that addresses many of these challenges. Data Lakes allow an organization to store all of their data, structured and unstructured, in one, centralized repository.
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cost effective, data storage, data collection, security, compliance, platform, big data, it resources
    
Amazon Web Services
Published By: VMware     Published Date: Sep 06, 2017
"By implementing the VMware App Volumes™ application management solution, OGL built a multitenant VDI environment that delivers an extensive range of applications to customers in real time, with full application functionality on any device, while also reducing OpEx and CapEx. Download this case study to learn how OGL Computer addressed these issues and more with VMware App Volumes: • Scale VDI service for more customers and applications. • Reduce expenses of Citrix VDI solution delivery. • Deliver and manage applications dynamically, in real time. • Give users desktop access on any Internet-connected device. "
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VMware
Published By: Oracle     Published Date: Jul 31, 2017
Consolidation in the healthcare industry has reached a record pace. The volume of organizational change has generated solid templates and best practices for change management. In addition, technological advances provide opportunities for sophisticated data analytics and systems integrations. By identifying and taking advantage of these technologies, healthcare organizations can increase the odds of successful integrations that result in greater agility decrease their cost base, and improve the quality of care they provide.
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Oracle
Published By: IBM     Published Date: Jul 26, 2017
To compete in today’s fast-paced business climate, enterprises need accurate and frequent sales and customer reports to make real-time operational decisions about pricing, merchandising and inventory management. They also require greater agility to respond to business events as they happen, and more visibility into business activities so information and systems are optimized for peak efficiency and performance. By making use of data capture and business intelligence to integrate and apply data across the enterprise, organizations can capitalize on emerging opportunities and build a competitive advantage. The IBM® data replication portfolio is designed to address these issues through a highly flexible one-stop shop for high-volume, robust, secure information replication across heterogeneous data stores. The portfolio leverages real-time data replication to support high availability, database migration, application consolidation, dynamic warehousing, master data management (MDM), service
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ibm, infosphere, data replication, security, data storage
    
IBM
Published By: Teradata     Published Date: May 02, 2017
A Great Use of the Cloud: Recent trends in information management see companies shifting their focus to, or entertaining a notion for the first time of a cloud-based solution. In the past, the only clear choice for most organizations has been on-premises data—oftentimes using an appliance-based platform. However, the costs of scale are gnawing away at the notion that this remains the best approach for all or some of a company’s analytical needs. This paper, written by McKnight Consulting analysts William McKnight and Jake Dolezal, describes two organizations with mature enterprise data warehouse capabilities, that have pivoted components of their architecture to accommodate the cloud.
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data projects, data volume, business data, cloud security, data storage, data management, cloud privacy, encryption, security integration
    
Teradata
Published By: VMware     Published Date: Feb 24, 2017
As the volume and variety of mobile devices surge, so do expectations among end users and business leaders to put these devices to work—as tools for productivity and a competitive advantage for the enterprise. With the goal of striking a balance between opportunity and control, increasing numbers of IT decision makers are adopting enterprise mobility management (EMM) solutions. So, how do you know if your organization is ready to make the move? Read this white paper to determine if now is the right time to adopt EMM, especially if your organization experiences: - Increased need for security and compliance - Device expansion - Rapid growth - And more
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VMware
Published By: VMware AirWatch     Published Date: Feb 21, 2017
By implementing the VMware App Volumes™ application management solution, OGL built a multitenant VDI environment that delivers an extensive range of applications to customers in real time, with full application functionality on any device, while also reducing OpEx and CapEx. Download this case study to learn how OGL Computer addressed these issues and more with VMware App Volumes: • Scale VDI service for more customers and applications. • Reduce expenses of Citrix VDI solution delivery. • Deliver and manage applications dynamically, in real time. • Give users desktop access on any Internet-connected device.
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VMware AirWatch
Published By: Dun & Bradstreet     Published Date: Feb 21, 2017
As the volume of data coming into organizations – from both internal and external sources – continues to grow and makes its way across departmental systems in many different formats, there is a critical need to create a single, holistic view of the key data entities in common use across the enterprise. Master Data Management (MDM) aims to accomplish this goal. Not surprisingly, MDM has become a significant priority for global enterprises, with the market expected to triple from $9.4B to $26.8B by 2020 according to analysts. The reality, though, is that while seemingly everyone is investing heavily in the tools to manage data, few are putting a great enough emphasis on the data itself. And that’s a problem. Poor data quality is said to be costing businesses $3.1 trillion annually – and that’s just in the US alone. The information being put into MDM tools must be mastered first and foremost.
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managing data, data management insight, mdm, master data management
    
Dun & Bradstreet
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