data driven enterprise

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By: MicroStrategy     Published Date: Jan 23, 2019
By 2025, the total amount of data produced will grow to 175 zettabytes, according to IDC’s Data Age 2025 Report. How will enterprises evolve over the next year to manage and make the most of this unprecedented growth? Download 10 Enterprise Analytics Trends to Watch in 2019 to learn how leading organizations will win with embedded and augmented analytics, HyperIntelligence, collaboration, enterprise AI strategies, and more. This eBook details the transformational technologies data-driven organizations will need to leverage to get and stay ahead in 2019 and beyond, with contributions from thought leaders, including: Mike Gualtieri of Forrester Research Ray Wang and Doug Henschen of Constellation Research Mark Smith and David Menninger of Ventana Research Chandana Gopal of IDC Ronald van Loon, and more. Is your organization ready for the data-driven future? Read 10 Enterprise Analytics Trends to Watch in 2019 today to find out.
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     MicroStrategy
By: MicroStrategy     Published Date: Apr 11, 2019
By 2025, the total amount of data produced will grow to 175 zettabytes, according to IDC’s Data Age 2025 Report. How will enterprises evolve over the next year to manage and make the most of this unprecedented growth? Download 10 Enterprise Analytics Trends to Watch in 2019 to learn how leading organizations will win with embedded and augmented analytics, HyperIntelligence, collaboration, enterprise AI strategies, and more. This eBook details the transformational technologies data-driven organizations will need to leverage to get and stay ahead in 2019 and beyond, with contributions from thought leaders, including: Mike Gualtieri of Forrester Research Ray Wang and Doug Henschen of Constellation Research Mark Smith and David Menninger of Ventana Research Chandana Gopal of IDC Ronald van Loon, and more. Is your organization ready for the data-driven future? Read 10 Enterprise Analytics Trends to Watch in 2019 today to find out.
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     MicroStrategy
By: MicroStrategy     Published Date: Aug 21, 2019
Ready or not, the future is here. For enterprise organizations, it must be a data-driven one. Whoever can use technology to transform the customer experience, and be the first to discover and deliver on new business models, will be the disruptor. Those who can’t, the disrupted in this period known as the “era of Digital Darwinism.” The future belongs to the Intelligent Enterprise which anticipates constantly evolving regulatory, technological, market, and competitive challenges and turns them into opportunity and profit. It delivers a single version of the truth and agility. It connects to any data and distributes reports to thousands. The Intelligent Enterprise goes beyond business intelligence, delivering transformative insight to every user, constituent and partner. Are most organizations there yet? As brands hone and focus their 2020 (and even 2030) vision, MicroStrategy has surveyed 500 enterprise analytics professionals on the state of their organization’s analytics initiatives.
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     MicroStrategy
By: Oracle     Published Date: Apr 22, 2015
This white paper distills six rules that modern CFOs worldwide are adopting to attract, retain and nurture finance talent with the skills needed to put finance at the heart of data driven business decision making across the enterprise.
Tags : digital, finance, modern finance, finance departments, attract finance talent, big data, cfos, modern business challenges
     Oracle
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
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
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
By: Workday     Published Date: Jun 05, 2017
In today’s mobile, connected and data-driven world, legacy financial management systems are failing to meet the needs of the modern enterprise.
Tags : workday, finance management, mobile employees, mobile workers, mobile data, cloud finance, cloud hr, hr technology
     Workday
By: Infosys     Published Date: Sep 12, 2019
Digital-born companies have challenged large long-established businesses across industries with newer data, AI-powered experiences, products/services. Sustained competitive advantage through customer ownership and seller power has since been significantly challenged and overturned. Customers are taking to newer AI and data-powered products/services in their pursuit of better experiences and exponentially higher value. This has triggered every company to challenge status-quo, unleash themselves from very structure of industry and embrace transformation in the new world. Data and AI have shaped themselves into a major economic force that is at the epicenter of transformation of every industry; through 3 horizons. Data, in the first horizon, was the key ingredient in driving more data-driven decisions. Data, in the second horizon, is playing a transformational role in the enterprises' pursuit of being Data Native Digital Native enterprise.
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     Infosys
By: SAS     Published Date: Mar 06, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
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     SAS
By: Datastax     Published Date: May 20, 2019
DataStax Enterprise and Apache Kafka are designed specifically to fit the needs of modern, next-generation businesses. With DataStax Enterprise (DSE) providing the blazing fast, highly-available hybrid cloud data layer and Apache Kafka™ detangling the web of complex architectures via its distributed streaming attributes, these two form a perfect match for event-driven enterprise architectures.
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     Datastax
By: Pure Storage     Published Date: Mar 15, 2018
Managing technology refreshes is not a popular task among enterprise storage administrators, although it is a necessary task for successful businesses. As a business evolves, managing more data and adding new applications in the process, enterprise storage infrastructure inevitably needs to grow in performance and capacity. Enterprise storage solutions have traditionally imposed limitations in terms of their ability to easily accommodate technology refreshes that keep infrastructure current and operating reliably and most cost effectively. In 2015, Pure Storage introduced a new technology refresh model that has driven strong change in the enterprise storage industry by addressing the major pain points of legacy models and provided overall a much more cost-effective life-cycle management approach. In conjunction with other aspects of Pure Storage's enterprise storage product and services offerings, the company's "Evergreen Storage" technology refresh model has contributed to this all-f
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     Pure Storage
By: Oracle     Published Date: Oct 20, 2017
What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i
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     Oracle
By: Carbonite     Published Date: Oct 10, 2018
Overview Key Challenges Organizations still struggle with communication between data owners and those responsible for administering DLP systems, leading to technology-driven — rather than business-driven — implementations. Many clients who deploy enterprise DLP systems struggle to get out of the initial phases of discovering and monitoring data flows, never realizing the potential benefits of deeper data analytics or applying appropriate data protections. DLP as a technology has a reputation of being a high-maintenance control — incomplete deployments are common, tuning is a never-ending process, lack of organization buy-in is low, and calculations of ROI are complex.
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     Carbonite
By: IBM     Published Date: May 26, 2017
Securing your infrastructure, your customer interactions and protecting your data are critical to preserving your reputation and your bottom line. Many cyber attacks remain undetected for up to eight months1 and can cost an organization an average of 11 million USD.2 Today’s cyber actors are becoming more sophisticated, agile and capable of getting past any network security. Organizations must evolve, replacing traditional defensive security strategies with a proactive, intelligence-driven offense to prevent and disrupt these threats. IBM® i2® Enterprise Insight Analysis is a next generation intelligence solution that enables organizations to incorporate cyber threat hunting into their security strategy and turn their defense into a proactive offense.It helps organizations uncover critical insights about their threats and threat actors so they can mitigate and counter more threats with a combination of multi-dimensional visualte analysis capabilities
Tags : ibm, ibm i2, cyber security, customer interaction, enterprise insight analysis
     IBM
By: NetApp     Published Date: Mar 11, 2015
To enable the data-driven enterprise, IT organizations are moving rapidly to a services-based cloud model. This white paper highlights the challenges of controlling data in hybrid as-a-service IT environments and suggests that data control in hybrid IT should be looked at as a framework rather than as a single effort.
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     NetApp
By: Infosys     Published Date: Sep 09, 2019
Infosys has embarked on a transformational journey to reinvent the way it and its clients do business. Like our most visionary clients, Infosys' goal is to become a completely knowledge- and data-driven organization, with agility built into its DNA so that it can quickly sense changing business needs and continuously evolve in response. But we are not there yet, and the road is challenging. We are envisioning Infosys to be a Live Enterprise powered by the Infosys Digital Platform. The vision with the digital platform is to provide everyone who uses it with a frictionless digital experience wherever they are in the world. Anytime, anywhere access will be completely scalable and secure, and will feature online and offline compatibility in a flawless, employee-centric manner.
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     Infosys
By: Dun & Bradstreet     Published Date: Apr 21, 2016
When the right approach is applied, analytics can drive more effective marketing strategies. While marketers understand the role analytics plays within the organization, most are not leveraging analytics to really drive enterprise performance. We surveyed 100+ business leaders to understand the state of analytics maturity across today’s leading organizations, uncovering common challenges teams are facing in their quest to use data and analytics to deliver a competitive advantage. What We Uncovered: - 73% of analytic professionals claim to work for an analytically-driven company - Only 42% of companies have a strategy for using analytics across the enterprise - Just 38% of companies share results of their analytic insights outside their department - 81% of organizations rely on 3rd parties for at least some portion of their analysis Download the report to learn how marketers, like yourself, view themselves in light of using analytics to drive their business.
Tags : hoover's, marketing strategies, analytics, data
     Dun & Bradstreet
By: Oracle ODA     Published Date: Dec 06, 2016
It’s no secret that data-driven business strategies have resulted in unprecedented data growth and management of more complex database structures. Not only that, but IT leadership continues to play a strategic role in the direction of the business, especially as these disruptive business strategies come into play. This white paper addresses some of the key considerations IT management should have as they evaluate their IT roadmap and infrastructure to meet these dynamic enterprise needs.
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     Oracle ODA
By: Equinix     Published Date: Jul 13, 2015
We're Equinix. We run global data centers that protect, connect and power the digital economy. This eBook is all about improving network performance. In it, we'll take a quick look at the current state of the information-driven world and the growing demands on enterprise networks. Then you'll learn about Equinix Performance Hub and the ways you can leverage it to optimize and future-proof your network. You'll pick up some tips and trends along the way, and we'll give you the opportunity to explore more links in each section, such as videos and analyst papers. So go ahead and dig in.
Tags : enterprise network, data centers, network performance, information-driven world, data management
     Equinix
By: Juniper Networks     Published Date: Feb 05, 2018
Innovative data-driven strategies are enabling organizations to connect with customers and increase operational efficiency as never before. These new initiatives are built on a multitude of applications, such as big-data analytics, supply chain, and factory automation. On average, organizations are now 53% digital as they create new ways of operating and growing their businesses, according to the Computerworld 2017 Forecast Study. As part of this transformation, enterprises rely increasingly on multivendor, multicloud environments that mix on-premise, private, and public cloud services and workloads. This shift is causing enterprises to increase network capacity; 55% of enterprises in the Computerworld study expect to add network bandwidth in the next 12 months.
Tags : security, automation, savings, technology, cloud
     Juniper Networks
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
By: Lookout     Published Date: Aug 28, 2017
The world has changed. Yesterday everyone had a managed PC for work and all enterprise data was behind a firewall. Today, mobile devices are the control panel for our personal and professional lives. This change has contributed to the single largest technology-driven lifestyle change of the last 10 years. As productivity tools, mobile devices now access significantly more data than in years past. This has made mobile the new frontier for a wide spectrum of risk that includes cyber attacks, a range of malware families, non-compliant apps that leak data, and vulnerabilities in device operating systems or apps. A secure digital business ecosystem demands technologies that enable organizations to continuously monitor for threats and provide enterprise-wide visibility into threat intelligence.
Tags : data protection, mobile risks, productivity tools, cyber attacks, device vulnerabilities
     Lookout
By: Datastax     Published Date: Aug 23, 2017
Kenzan, a software engineering firm that specializes in building scalable, data-driven solutions, often leverages DataStax Enterprise (DSE) for customers that have high expectations for both performance and value. That means making careful, informed choices when designing the cloud infrastructure that applications run on. Controlling costs is always a priority for businesses that rely on AWS for running DSE. With AWS, it can be tempting to solve performance issues simply by adding more resources until the problem goes away. However, this “solution” results in increased costs which quickly add up over time. In this white paper, Kenzan and DataStax identify some of the key factors to consider when building out infrastructure on AWS, outlining practical steps you can take to optimize performance with DSE on AWS while keeping costs in check.
Tags : enterprise, benchmarking, data
     Datastax
By: Simba by Magnitude     Published Date: Jul 12, 2019
Today’s C-level executives expect data and analytics to provide them with speed and agility to deliver competitive advantage and to disrupt new markets. But, in today’s complex data environment exists a near paradox between these expectations, that companies will be able to rapidly deliver value using data and analytics--and the complexities of the data landscape, making it more difficult to find, govern, connect to and access the data needed to deliver that value. Once thing is clear: if management expectation is to be met, simplifying connectivity is a must.In this white paper, veteran analyst Mike Ferguson, Managing Director of Intelligent Business Strategies explores how simplifying data access –connectivity –aligns expectations with data realities thus decreasing time to value.
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     Simba by Magnitude
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