cross enterprise data

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Published By: Dell EMC Storage     Published Date: Aug 15, 2019
The digital era has ushered in a proliferation of data that powers modern businesses. When leveraged properly, organizations are seeing the potential of data to drive better outcomes across all aspects of their business. Using data to support different workflows, analytics, and activities transforms it into data capital — a digital asset that will drive value for the business. The extent to which an enterprise aligns its organization around this data capital mindset — in both the way they use data and the way they invest in data technology — can have lasting impacts on the success of the business. In February 2019, Dell EMC and Intel commissioned Forrester Consulting to evaluate whether the ability to harness and apply data and analytics at every opportunity is fast becoming a prerequisite for success. To test this, Forrester conducted a global survey of 516 IT decision makers. The survey found that companies with more mature data capital practices — leveraging more data types, managin
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Dell EMC Storage
Published By: ttec     Published Date: Jul 24, 2019
Data drives decision making across the enterprise. For sales executives, it’s critical to have information about where to focus outreach and understand what potential customers are looking for. But having data for its own sake won’t do much good. With advanced tools and a customerfocused mindset, companies are learning things about prospects never before possible. Thanks to advanced insights and machine learning that process algorithms and crunch millions of data points, new purchase patterns and propensity models are emerging to guide sales leaders as to what will work best for their business. Read this paper to learn how to act on advanced insight in the sales and marketing process. Highlights include: The enormous potential of new data tools and analysis Resources needed to act on the insight Company examples Strategic and operational recommendations
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ttec
Published By: Pure Storage     Published Date: Apr 10, 2019
Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data
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Pure Storage
Published By: Flexera     Published Date: Feb 19, 2019
Flexera’s Software Vulnerability Research allows effective reduction of the attack surface for cybercriminals, providing access to verified vulnerability intelligence from Secunia Research covering all applications and systems across all platforms. It drives a prioritized remediation process by handling vulnerability workflows, tickets and alerts, and describes the steps to mitigate the risk of costly breaches. You Don’t Know What You Don’t Know It’s hard for enterprise security analysts to get reliable and trusted information about software vulnerabilities and then identify and filter that data for just the products that matter to their organization. Those challenges lead to wasted time and effort. Learn more.
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Flexera
Published By: Pure Storage     Published Date: Oct 09, 2018
Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data.
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Pure Storage
Published By: Group M_IBM Q418     Published Date: Oct 02, 2018
Across enterprises of all kinds, data is multiplying rapidly in both quantity and variety. Across multi-cloud environments, new sources are exponentially increasing the growing stream of information, including the Internet of Things, social media, mobile devices, virtual reality implementations and optical tracking.
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Group M_IBM Q418
Published By: Carbonite     Published Date: Jul 18, 2018
© 2018 Carbonite, Inc. All rights reserved. Case study Diamond Foods’ Diamond of California® nuts are household staples for shoppers across the U.S. But constantly filling grocery store shelves with snacks requires intricate supply chain management that relies on critical business data, including complex spreadsheets and enterprise resource planning files, to keep production and deliveries on schedule. “If our critical servers go down or we lose important data on employee laptops, it has a direct impact on our bottom line,” says Kentrell Davis, Senior Client Support Services Analyst at Diamond Foods.
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Carbonite
Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
Artificial intelligence (AI) seems to be on everyone’s mind. It powers natural language recognition within voice-powered assistants like Siri and Alexa, beats world-class Go players, and enables hyper-targeted e-commerce and content recommendations across the web, as we see with Amazon and Netflix. But recently, AI has begun actively expanding its footprint within the enterprise. Executives are trying to more fully comprehend what AI is and how they can use its insights into their data to better capitalize on business opportunities. This additional information can enable engaging with customers more productively and efficiently, forming an edge against the competition. Read more in our AI survey summary.
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artificial, intelligence, enterprise
    
BlackBerry Cylance
Published By: Vehicle Tracking Solutions     Published Date: May 31, 2018
When implementing an enterprise fleet management and telematics solution, enterprise fleets, large and small, see significant value, cost-savings, and operational excellence that result in maximized profits across your organization's bottom line. This guide will assist you in learning about the wide range of benefits from a dynamic enterprise fleet management and telematics software and the latest features empowering fleets to make data-driven decisions that improve safety, efficiency, and productivity to drive long-term quantifiable success.
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Vehicle Tracking Solutions
Published By: CA Technologies EMEA     Published Date: May 23, 2018
Increasingly, enterprises are opening their data and applications to partners, developers, mobile apps and cloud services. APIs provide a standardized way to open up information assets across the web, mobile devices, serviceoriented architecture (SOA) and the cloud. However, to make API information sharing safe, reliable and cost-effective, enterprises must deal with critical security, performance management and data adaptation challenges. CA API Management combines advanced functionality for back-end integration, mobile optimization, cloud orchestration and developer management. It is unique in its ability to address the full breadth of enterprise API management challenges.
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CA Technologies EMEA
Published By: Pure Storage     Published Date: Apr 18, 2018
Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data. Amazon CEO Jeff Bezos spoke about the potential of artificial intelligence and machine learning at the 2017 Internet Association‘s annual gala in Washington, D.C., “It is a renaissance, it is a golden age,” Bezos said. “We are solving problems with machine learning and artificial intelligence that were in the realm of science fiction for the last several decades. Natural language understanding, machine vision problems, it really is an amazing renaissance.” Machine learning and AI is a horizontal enabling layer. It will empower and improve every business, every government organization, every philanthropy
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Pure Storage
Published By: Oracle     Published Date: Nov 28, 2017
Today’s leading-edge organizations differentiate themselves through analytics to further their competitive advantage by extracting value from all their data sources. Other companies are looking to become data-driven through the modernization of their data management deployments. These strategies do include challenges, such as the management of large growing volumes of data. Today’s digital world is already creating data at an explosive rate, and the next wave is on the horizon, driven by the emergence of IoT data sources. The physical data warehouses of the past were great for collecting data from across the enterprise for analysis, but the storage and compute resources needed to support them are not able to keep pace with the explosive growth. In addition, the manual cumbersome task of patch, update, upgrade poses risks to data due to human errors. To reduce risks, costs, complexity, and time to value, many organizations are taking their data warehouses to the cloud. Whether hosted lo
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Oracle
Published By: Cisco EMEA     Published Date: Nov 13, 2017
The HX Data Platform uses a self-healing architecture that implements data replication for high availability, remediates hardware failures, and alerts your IT administrators so that problems can be resolved quickly and your business can continue to operate. Space-efficient, pointerbased snapshots facilitate backup operations, and native replication supports cross-site protection. Data-at-rest encryption protects data from security risks and threats. Integration with leading enterprise backup systems allows you to extend your preferred data protection tools to your hyperconverged environment.
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hyperflex, systems, data platform, storage efficiency, business, cisco
    
Cisco EMEA
Published By: IBM     Published Date: Oct 17, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive (MiFID2). Many of these new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data
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IBM
Published By: IBM     Published Date: Oct 03, 2017
Many new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data. To keep pace with regulatory changes, many banks will need to reapportion their budgets to support the development of new systems and processes. Regulators continually indicate that the banks must be able to provide, secure and deliver high-quality information that is consistent and mature.
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data aggregation, risk reporting, bank regulation, enterprise, reapportion budgets
    
IBM
Published By: CA Technologies     Published Date: Aug 22, 2017
Across industry sectors, the boundaries of the traditional enterprise are blurring, as organizations open up their on-premise data and application functionality to partner organizations, the Web, mobile apps, smart devices and the cloud. APIs (application programming interfaces) form the foundation of this new open enterprise, allowing enterprises to reuse their existing information assets across organizational boundaries.
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CA Technologies
Published By: Juniper Networks     Published Date: Aug 08, 2017
As enterprises embark on the digital transformation to take advantage of artificial intelligence, big data, machine learning, IoT, and cloud, they need a network infrastructure that gives them a solid foundation. Juniper Networks® Unite CloudEnabled Enterprise allows networking across your entire enterprise—campus, branch, and data center—ultimately helping you reduce risk, increase agility, lower costs, and enhance the customer experience. Here are the Top 6 reasons why enterprises embarking on the journey of digital transformation should switch to the Juniper Unite Cloud-Enabled Enterprise solution.
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Juniper Networks
Published By: Juniper Networks     Published Date: Aug 08, 2017
As the business turns to IT to enhance operational efficiency across the enterprise network—spanning the campus, data center, and branch—no organization can afford for its network to serve as the weak link. This IP Networking Comparison Guide examines four key aspects of the comprehensive enterprise network and looks at key factors within each area. This document will give you a clear perspective on how the various options stack up on the most important features and capabilities necessary to empower innovation.
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Juniper Networks
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: IBM APAC     Published Date: Jul 09, 2017
Organizations today collect a tremendous amount of data and are bolstering their analytics capabilities to generate new, data-driven insights from this expanding resource. To make the most of growing data volumes, they need to provide rapid access to data across the enterprise. At the same time, they need efficient and workable ways to store and manage data over the long term. A governed data lake approach offers an opportunity to manage these challenges. Download this white paper to find out more.
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data lake, big data, analytics
    
IBM APAC
Published By: Juniper Networks     Published Date: May 17, 2017
As the business turns to IT to enhance operational efficiency across the enterprise network—spanning the campus, data center, and branch—no organization can afford for its network to serve as the weak link.
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Juniper Networks
Published By: IBM     Published Date: Apr 18, 2017
The data integration tool market was worth approximately $2.8 billion in constant currency at the end of 2015, an increase of 10.5% from the end of 2014. The discipline of data integration comprises the practices, architectural techniques and tools that ingest, transform, combine and provision data across the spectrum of information types in the enterprise and beyond — to meet the data consumption requirements of all applications and business processes. The biggest changes in the market from 2015 are the increased demand for data virtualization, the growing use of data integration tools to combine "data lakes" with existing integration solutions, and the overall expectation that data integration will become cloud- and on-premises-agnostic.
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data integration, data security, data optimization, data virtualization, database security, data analytics, data innovation
    
IBM
Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
Complexity, globalization and digitalization are just some of the elements at play in the risk landscape—and data is becoming a core part of understanding and navigating risk. How do modern finance leaders view, navigate and manage enterprise risk with data? Dun & Bradstreet surveyed global finance leaders across industries and business types. Here are the top trends that emerged from the study: 1. The Enterprise Risk & Strategy Disconnect—Finance leaders are using data and managing risk programs, but over 65% of finance leaders say there’s missing link between risk and strategy. 2. The Risks of the Use and Misuse of Data—Up to 50% of the data used to manage modern risk is disconnected. Only 15% of leaders are confident about the quality of their data. 3. Risky Relationships—Only 20% of finance leaders say the data they use to manage risk is fully integrated and shared. Download the study to learn how finance leaders are approaching data and enterprise risk management
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Dun & Bradstreet
Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
Stories and statistics behind successful analytics projects The adoption of analytics across the enterprise is accelerating, and with good reason. Analytics can offer a competitive advantage by helping to identify growth opportunities, circumnavigate risk and improve customer relationships. These insights are becoming crucial parts of the business strategy for executives representing a wide array of industries. Check out our latest eBook to see how some of the world’s leading companies are using analytics to meet their needs. You’ll receive diverse examples of how organizations applied the latest statistical methodologies, such as: scorecard build, regression, decision trees, machine learning and material change to uncover meaning in data. The examples represent global brands across critical industries – Financial Services, Insurance, High-Tech, Aerospace, Manufacturing and others – where analytics helped answer their most challenging questions.
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Dun & Bradstreet
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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