enterprises

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Published By: Datawatch     Published Date: Apr 06, 2018
Enterprises are focusing on becoming ever more data-driven, meaning that it is simply unacceptable to allow data to go to waste. Yet, as the amount of data businesses collect and control continues to increase exponentially, many organizations are failing to derive enough business value from their data. Companies are feeling the pressure to extract maximum value from all of their data, both defensive and offensive. Defensive analytics are the “plumbing aspects” of data management that must be captured to mitigate risk and establish a basic understanding of business performance. Offensive analytics build on defensive analytics and support overarching business objectives, strategic initiatives and long-term goals using predictive models. In this whitepaper, you will learn how to address many challenges, including streamlining operational reporting, delivering insight and providing a single, unified platform for everyone.
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Datawatch
Published By: Bitwise     Published Date: Apr 30, 2018
Organizations that adopt an enterprise data lake model for real-time, self-service and advanced analytics require a fresh approach and outlook to develop a Data Governance strategy as Hadoop changes the way that organizations ingest and store data, as well as how business partners access and use data. This paper outlines pillars for Hadoop Data Governance and Security that provide a framework that can be applied to any company.
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Bitwise
Published By: Trillium Software     Published Date: Oct 26, 2015
Acting Quickly – Or Not at All The pace of business is accelerating. Enterprises must do more things, do them more quickly – and then adjust to market and competitive forces and do them differently. They must adapt in order to remain differentiated, and with that differentiation, hopefully build and sustain competitive advantage.
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Trillium Software
Published By: DATAVERSITY     Published Date: Jul 06, 2015
The growth of NoSQL data storage solutions have revolutionized the way enterprises are dealing with their data. The older, relational platforms are still being utilized by most organizations, while the implementation of varying NoSQL platforms including Key-Value, Wide Column, Document, Graph, and Hybrid data stores are increasing at faster rates than ever seen before. Such implementations are causing enterprises to revise their Data Management procedures across-the-board from governance to analytics, metadata management to software development, data modeling to regulation and compliance. The time-honored techniques for data modeling are being rewritten, reworked, and modified in a multitude of different ways, often wholly dependent on the NoSQL platform under development. The research report analyzes a 2015 DATAVERSITY® survey titled “Modeling NoSQL.” The survey examined a number of crucial issues within the NoSQL world today, with focus on data modeling in particular.
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DATAVERSITY
Published By: MarkLogic     Published Date: Jun 17, 2015
Modern enterprises face increasing pressure to deliver business value through technological innovation that leverages all available data. At the same time, those enterprises need to reduce expenses to stay competitive, deliver results faster to respond to market demands, use real-time analytics so users can make informed decisions, and develop new applications with enhanced developer productivity. All of these factors put big data at the top of the agenda. Unfortunately, the promise of big data has often failed to deliver. With the growing volumes of unstructured and multi-structured data flooding into our data centers, the relational databases that enterprises have relied on for the last 40-years are now too limiting and inflexible. New-generation NoSQL (“Not Only SQL”) databases have gained popularity because they are ideally suited to deal with the volume, velocity, and variety of data that businesses and governments handle today.
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data, data management, databse, marklogic, column store, wide column store, nosql
    
MarkLogic
Published By: TopQuadrant     Published Date: Mar 21, 2015
Data management is becoming more and more central to the business model of enterprises. The time when data was looked at as little more than the byproduct of automation is long gone, and today we see enterprises vigorously engaged in trying to unlock maximum value from their data, even to the extent of directly monetizing it. Yet, many of these efforts are hampered by immature data governance and management practices stemming from a legacy that did not pay much attention to data. Part of this problem is a failure to understand that there are different types of data, and each type of data has its own special characteristics, challenges and concerns. Reference data is a special type of data. It is essentially codes whose basic job is to turn other data into meaningful business information and to provide an informational context for the wider world in which the enterprise functions. This paper discusses the challenges associated with implementing a reference data management solution and the essential components of any vision for the governance and management of reference data. It covers the following topics in some detail: · What is reference data? · Why is reference data management important? · What are the challenges of reference data management? · What are some best practices for the governance and management of reference data? · What capabilities should you look for in a reference data solution?
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data management, data, reference data, reference data management, top quadrant, malcolm chisholm
    
TopQuadrant
Published By: TopQuadrant     Published Date: Jun 01, 2017
This paper presents a practitioner informed roadmap intended to assist enterprises in maturing their Enterprise Information Management (EIM) practices, with a specific focus on improving Reference Data Management (RDM). Reference data is found in every application used by an enterprise including back-end systems, front-end commerce applications, data exchange formats, and in outsourced, hosted systems, big data platforms, and data warehouses. It can easily be 20–50% of the tables in a data store. And the values are used throughout the transactional and mastered data sets to make the system internally consistent.
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TopQuadrant
Published By: CA Technologies     Published Date: Apr 24, 2013
Using ERwin Data Modeler & Microsoft SQL Azure to Move Data to the Cloud within the DaaS Lifecycle by Nuccio Piscopo Cloud computing is one of the major growth areas in the world of IT. This article provides an analysis of how to apply the DaaS (Database as a Service) lifecycle working with ERwin and the SQL Azure platform. It should help enterprises to obtain the benefits of DaaS and take advantage of its potential for improvement and transformation of data models in the Cloud. The use case introduced identifies key actions, requirements and practices that can support activities to help formulate a plan for successfully moving data to the Cloud.
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CA Technologies
Published By: AT&T     Published Date: Sep 11, 2014
The age of Big Data is upon us. Storage costs are going down, and data analytics is becoming more capable and more user-friendly. Even your auto mechanic will be storing a petabyte of data soon. Big Data will give businesses new insights and help improve operations. With these new tools come questions about how to use them. But your mechanic knows more about fixing a transmission than developing a Hadoop cluster, and similar concerns hold true for larger enterprises. Businesses everywhere are looking for guidance.
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AT&T
Published By: iCEDQ     Published Date: Feb 05, 2015
The demand for using data as an asset has grown to a level where data-centric applications are now the norm in enterprises. Yet data-centric applications fall short of user expectations at a high rate. Part of this is due to inadequate quality assurance. This in turn arises from trying to develop data-centric projects using the old paradigm of the SDLC, which came into existence during an age of process automation. SDLC does not fit with data-centric projects and cannot address the QA needs of these projects. Instead, a new approach is needed where analysts develop business rules to test atomic items of data quality. These rules have to be run in an automated fashion in a business rules engine. Additionally, QA has to be carried past the point of application implementation and support the running of the production environment.
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data, data management, data warehousing, data quality, etl testing, malcolm chisholm
    
iCEDQ
Published By: Reltio     Published Date: Jan 20, 2017
If you invested in master data management (MDM), you are part of an elite association of those who have been able to afford the time, effort and resources to deploy what has characteristically been a tool, and discipline reserved for only the largest enterprises. Feedback from top industry analysts and companies that transitioned from legacy MDM to modern data management platforms, led to the compilation of a list of 10 warning signs you can use as a handy guide. If one or more of these signs get your attention, it warrants a serious conversation with your current provider about these issues, and how they compare to modern offerings available today.
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Reltio
Published By: Innovative Systems     Published Date: Oct 26, 2017
Even after investing significant time and resources implementing a data quality solution, many enterprises find that their data does not effectively support their goals. This white paper shows how to get the most out of your data quality solution by tailoring it to support your business goals.
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Innovative Systems
Published By: AtomRain     Published Date: Nov 07, 2017
The world is more connected than ever before, and data relationships only continue to multiply. Yet enterprises still operate largely with an incomplete perspective caused by segmented, non-contextual and disconnected data silos. Connected data is the key to surviving, growing and thriving. However, a transformation across the entire enterprise won’t happen overnight, and each step must be measurable from both a business and technical perspective. Organizations need expert guidance to move more swiftly and avoid costly technical pitfalls in the new paradigm. This paper examines the journey to what we call, “The Connected Enterprise”.
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AtomRain
Published By: MapR Technologies     Published Date: Jul 26, 2013
Enterprises are faced with new requirements for data. We now have big data that is different from the structured, cleansed corporate data repositories of the past.Before, we had to plan out structured queries. In the Hadoop world, we don’t have to sort data according to a predetermined schema when we collect it. We can store data as it arrives and decide what to do with it later. Today, there are different ways to analyze data collected in Hadoop—but which one is the best way forward?
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white paper, hadoop, nosql, mapr, mapr technologies
    
MapR Technologies
Published By: Oracle     Published Date: Feb 28, 2018
There is no doubt that enterprise cloud is a new and improved IT strategy. Cloud services have proven to improve organizational agility and reduce the burden of IT infrastructure and cost. Moving to the cloud is no longer a question of “if” but “when” and “how.” Most enterprises we interviewed are moving to cloud in phases over time and matching workloads to their perceptions of a vendor’s cloud capabilities that will best support their objectives. Many will require the ability and flexibility to support multivendor cloud and multiple deployment choices (e.g., public cloud, private cloud, and hybrid cloud).
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cloud, enterprise, scale, infrastructure
    
Oracle
Published By: Juniper Networks     Published Date: May 04, 2018
PwC surveyed 235 IT leaders and interviewed another 35 from large, medium, and small enterprises to understand the buying decisions of IT leaders, across a wide variety of networking components (i.e., switches, SDN, and infrastructure monitoring solutions) within the data center. This report highlights the survey and interview insights to help Enterprise IT leaders understand the trends and implications of multi cloud environments.
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Juniper Networks
Published By: Google     Published Date: Apr 30, 2018
"In a recent global survey conducted on behalf of Google Cloud in association with MIT SMR Custom Studio, respondents were asked: over the last two years, how has your overall confidence in the security of cloud applications and infrastructure changed? The response was encouraging. 74% of respondents have become more confident in cloud security. The age of unthinking fears about cloud security is over. Not only is cloud adoption rising steadily across geographies, industries and job functions, but confidence in cloud security is rising as well — to the point where increased security is a major reason enterprises opt for cloud solutions. Download this report and find out more."
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Google
Published By: Sage Software (APAC)     Published Date: May 02, 2018
Forward-looking enterprises are deciding to replace their legacy systems with more modern enterprise management solutions that provide a better way to manage the entire business, at a lower cost and on a global scale. Sage Business Cloud Enterprise Management solution is changing how enterprises compete and grow, by delivering faster, simpler and flexible enterprise management, at a fraction of the cost and complexity of typical enterprise ERP systems. Break free from the constraints of traditional ERP solutions and discover how Sage Business Cloud Enterprise Management can accelerate your business.
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Sage Software (APAC)
Published By: Carbonite     Published Date: Jan 04, 2018
Malware that encrypts a victim’s data until the extortionist’s demands are met is one of the most common forms of cybercrime. And the prevalence of ransomware attacks continues to increase. Cybercriminals are now using more than 50 different forms of ransomware to target and extort money from unsuspecting individuals and businesses. Ransomware attacks are pervasive. More than 4,000 ransomware attacks happen every day, and the volume of attacks is increasing at a rate of 300 percent annually. According to an IDT911 study, 84 percent of small and midsize businesses will not meet or report ransomware demands. No one is safe from ransomware, as it attacks enterprises and SMBs, government agencies, and individuals indiscriminately. While ransomware demands more than doubled in 2016 to $679 from $294 in 2015, the cost of remediating the damage and lost productivity is many multiples higher.
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Carbonite
Published By: Carbon Black     Published Date: Apr 10, 2018
With breaches today often going undetected for months or years, many organizations must now accept the very real possibility that intruders have already compromised their systems, regardless of the organization’s security posture. Today, compromises are measured in minutes and the speed of response is measured in days. Enterprises the world over are realizing that to close the gap, they need to evolve their security operations from being a largely reactive unit (waiting for alerts that indicate a threat) to being proactively on the hunt for new attacks that have evaded detection. When an incident does occur, the speed of your response will dictate the extent to which you can minimize the impact. In the case of a malicious attack, it takes on average over 7 months to identify a breach, and nearly two and a half additional months to contain the incident. Every second counts, and while the clock is ticking, the cost of the breach is rapidly increasing as well. Breaches that take over 3
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Carbon Black
Published By: MobileIron     Published Date: Nov 14, 2017
This paper covers some of the critical security gaps today’s mobile-cloud enterprises must address: • Unsecured devices. Unsecured devices allow users to easily access business data from mobile apps or cloud services simply by entering their credentials into an app or browser on the device. Once on the device, data can be easily compromised or shared with unauthorized, external sources. • Unmanaged apps. These typically include business apps, such as Office 365 productivity apps, that the user has downloaded from a personal app store instead of the enterprise app store. As a result, these apps are not under IT control but can still be used to access business content once the user enters his or her credentials. • Unsanctioned cloud services. Most enterprise cloud services have associated ecosystems of apps and services that integrate using APIs. While the enterprise cloud service might be sanctioned, apps and services from its ecosystem might not be.
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MobileIron
Published By: MobileIron     Published Date: May 07, 2018
The types of threats targeting enterprises are vastly different than they were just a couple of decades ago. Today, successful enterprise attacks are rarely executed by the “lone wolf” hacker and instead come from highly sophisticated and professional cybercriminal networks. These networks are driven by the profitability of ransomware and the sale of confidential consumer data, intellectual property, government intelligence, and other valuable data. While traditional PC-based antivirus solutions can offer some protection against these attacks, organizations need highly adaptive and much faster mobile threat defense (MTD) for enterprise devices.
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mobile, threat, detection, machine, ransomware, confidential, networks
    
MobileIron
Published By: MobileIron     Published Date: May 07, 2018
Enterprises and users continue to be concerned about mobile apps and mobile malware because they have been trained by legacy antivirus software packages. Look for a known malware file and remove it. The issue with this logic on mobile devices is the mobile operating systems evolve and add features very rapidly. The mobile operating systems add millions of lines of code in a year and therefore introduce unintended consequences, bugs and vulnerabilities. In 2017, there were more CVEs registered for Android and iOS than all of 2016 and 2015 combined. In 2017 there were 1229 CVEs awarded. Over half of these CVEs that received scores of 7 or greater indicated that the vulnerabilities are severe and exploitable. This trend is expected to continue as the mobile operating systems mature and more features are added.
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global, threat, report, mobile, malware, software, antivirus
    
MobileIron
Published By: Genesys     Published Date: Feb 21, 2018
Artificial intelligence (AI) can’t replicate the human touch, but it can ease your agents’ burden by handling many simple, repetitive requests. A new Forrester Consulting paper offers a look at the strengths and weaknesses of both AI and humans independently, yet how blending them together can give your customers the seamless end-to-end experience they expect. See how enterprises around the world use AI to improve customer service and uncover new revenue streams, the challenges they overcame, and why a blended solution with live agents makes sense. Download the paper to learn three key recommendations on using AI to improve agent productivity, agent satisfaction, and customer satisfaction.
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forrester, artificial intelligence, consulting, customer experience
    
Genesys
Published By: Genesys     Published Date: Feb 21, 2018
In the ongoing evolution of the customer experience, organizations continue to rely on phone and email while introducing new customer engagement channels. With the channel mix rapidly changing, it has become more important than ever to accurately identify and proactively deploy the next-best channels for engaging customers today and tomorrow. Gartner Research has profiled 15 ways that organizations will engage customers over the next 20 years. This includes augmented reality, virtual reality and mixed reality immersive solutions which will be adopted by 20% of large enterprises by 2020. By learning which engagement channels will best meet your customers’ needs in the future and prioritizing those aligned with your business model, you can improve customer engagement and
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gartner, customer engagement, customer experience, gartner research
    
Genesys
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