analytics organizations

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Published By: Infinidat EMEA     Published Date: May 14, 2019
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
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Infinidat EMEA
Published By: Sitecore     Published Date: Nov 04, 2009
This report highlights the strategic value of a next generation web content management system integrated with lead scoring, email marketing, customer relationship management, and web analytics. The report links the technology and practices of Best-in-Class organizations to engage customers, provide personalized experiences and manage the lead lifecycle.
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sitecore, aberdeen, lifecycle management, web content management, analytics, crm, emarketing, email marketing, lead generation
    
Sitecore
Published By: SAP     Published Date: Feb 03, 2017
To better understand the benefits, costs, and risks associated with implementation of SAP Business Objects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to provide the conclusions of this cost and benefit analysis.
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SAP
Published By: SAP     Published Date: Feb 03, 2017
To better understand the benefits, costs, and risks associated with implementation of SAP BusinessObjects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to report cost and benefit findings
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SAP
Published By: Zaloni     Published Date: Apr 24, 2019
Why your data catalog wont deliver significant ROI According to Gartner, organizations that provide access to a curated catalog of internal and external data assets will derive twice as much business value from their analytics investments by 2020 than those that do not. Thats a ringing endorsement of data catalogs, and a growing number of enterprises seem to agree. In fact, the global data catalog market is expected to grow from US$210.0 million in 2017 to US$620.0 million by 2022, at a Compound Annual Growth Rate (CAGR) of 24.2%. Why such large and intensifying demand for data catalogs? The primary driver is that many organizations are working to modernize their data platforms with data lakes, cloud-based data warehouses, advanced analytics and various SaaS applications in order to grow profitable digital initiatives. To support these digital initiatives and other business imperatives, organizations need more reliable, faster access to their data. However, modernizing data plat
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Zaloni
Published By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
With the maturing of the all-flash array (AFA) market, the established market leaders in this space are turning their attention to other ways to differentiate themselves from their competition besides just product functionality. Consciously designing and driving a better customer experience (CX) is a strategy being pursued by many of these vendors.This white paper defines cloud-based predictive analytics and discusses evolving storage requirements that are driving their use and takes a look at how these platforms are being used to drive incremental value for public sector organizations in the areas of performance, availability, management, recovery, and information technology (IT) infrastructure planning.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Apr 26, 2019
With the maturing of the all-flash array (AFA) market, the established market leaders in this space are turning their attention to other ways to differentiate themselves from their competition besides just product functionality. Consciously designing and driving a better customer experience (CX) is a strategy being pursued by many of these vendors.This white paper defines cloud-based predictive analytics and discusses evolving storage requirements that are driving their use and takes a look at how these platforms are being used to drive incremental value for public sector organizations in the areas of performance, availability, management, recovery, and information technology (IT) infrastructure planning.
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Hewlett Packard Enterprise
Published By: Hitachi Vantara     Published Date: Mar 08, 2019
Consider the key trends driving the modernization of the data infrastructure: focus on governance, mobilization and analytics. And take a look at the technologies that make up modern data infrastructure, including artificial intelligence (AI), flash storage, converged and hyperconverged platforms, and software-defined infrastructures. Read this e-book to observe the key trends driving the modernization of data infrastructure and see how organizations are adapting and flourishing in a data-driven world.
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Hitachi Vantara
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem. Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.
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Hewlett Packard Enterprise
Published By: SAP     Published Date: May 18, 2014
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, it management, knowledge management
    
SAP
Published By: HPE Intel     Published Date: Mar 15, 2016
As more enterprises adopt technologies such as cloud, mobile, and analytics to help achieve strategic competitive advantage, CIOs and IT managers must support business-critical processes at a very high level across the enterprise. At the same time, IT organizations must manage complex hybrid IT infrastructures that include both cloud and on-premises technologies from multiple vendors and support providers. IDC believes that to tackle these challenges, IT organizations should look to support providers for comprehensive offerings to help optimize IT operations and improve the efficiency of IT service delivery. In addition, IDC recommends that IT organizations looking to manage rapid change in todays IT landscape consider support providers with a record of innovative support services and a focus on advanced technology in support delivery.
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HPE Intel
Published By: Oracle     Published Date: Nov 28, 2017
Todays 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. Todays 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: SAS     Published Date: Jan 17, 2018
For many of us, the term smart city conjures up images of sensors collecting data about everything from traffic patterns to energy use. Its common for government leaders to think, Thats not for us. Were not there yet. But if your organization is collecting data of any kind, you are in a position to use that data to create a smarter city for your citizens. Download this whitepaper for 10 examples of analytics being used to solve problems or simplify tasks for government organizations.
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SAS
Published By: SAS     Published Date: Jan 17, 2018
This RSR custom research report explores the impact of omnichannel methods on merchandising, marketing and the supply chain; specifically, what analytical capabilities address the challenges that omnichannel selling and fulfillment pose for retailers. Consumers today routinely begin their shopping journeys online, but complete their purchases in nearby stores, in their home stores or delivered directly to their doors. Retail analytics enables organizations to capture data from their customers' journeys. Retailers that successfully deliver relevant omnichannel experiences while gaining a more sophisticated understanding of demand (where and how it is initiated) will enhance their brands value and create compelling and profitable customer relationships.
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SAS
Published By: SAS     Published Date: Jan 17, 2018
Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally. Learn more about key findings, including: Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics. Return on investment for analytics stems from the governing and sharing of data throughout the organization. Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.
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SAS
Published By: SAS     Published Date: Jan 17, 2018
This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.
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SAS
Published By: Pentaho     Published Date: Nov 04, 2015
Although the phrase next-generation platforms and analytics can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and todays reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
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pentaho, analytics, platforms, hadoop, big data, predictive analytics, networking, it management, knowledge management, data management
    
Pentaho
Published 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? Its 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
Published By: Oracle CX     Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
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Oracle CX
Published By: Oracle CX     Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle CX
Published By: SAS     Published Date: Oct 22, 2015
The Internet of Things (IoT) presents an opportunity to collect real-time information about every physical operation of a business. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors can deliver this information in real time. There is tremendous opportunity for those businesses that can convert raw IoT data into business insights, and the key to doing so lies within effective data analytics. To research the current state of IoT analytics, Blue Hill Research conducted deep qualitative interviews with three organizations that invested significant time and resources into their own IoT analytics initiatives. By distilling key themes and lessons learned from peer organizations, Blue Hill Research offers our analysis so that business decision makers can ultimately make informed investment decisions about the future of their IoT analytics projects.
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SAS
Published By: SAS     Published Date: Nov 04, 2015
In a panel discussion at the 12th annual SAS Health Analytics Executive Forum in May 2015, leaders from Dignity Health, Horizon Blue Cross Blue Shield of New Jersey, Janssen Pharmaceuticals and SAS shared what they have done to prove the value of analytics to their business leaders and what has worked for them as they developed an analytic culture in their organizations and put analytic insights to work.
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sas, healthcare, healthcare models, episode analytics, analytics, data management
    
SAS
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 worlds leading companies are using analytics to meet their needs. Youll 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: GE Healthcare     Published Date: Aug 27, 2015
This paper will explore some of the market dynamics driving the financial volatility in healthcare and will explore how advanced analytics, with the right IT backbone and organizational competencies, can help organizations successfully identify ways to manage revenue cycle profitability.
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centricity business, financial management, analytics, revenue cycle, hospital billing, hospital finance, patient billing, rcm, episodic payment, accountable care, icd-10, healthcare reform, shared savings, capitation, payment reform, risk based contracting, hospital consolidation, [mjm] claims, denials, cost to collect
    
GE Healthcare
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