HIT Consultant Insightful coverage of healthcare innovation
 

analytics organizations

Results 101 - 125 of 208Sort Results By: Published Date | Title | Company Name
Published By: Oracle     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
Tags : 
    
Oracle
Published By: Pentaho     Published Date: Apr 28, 2016
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 today’s 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.
Tags : 
pentaho, best practices, hadoop, next generation analytics, platforms, infrastructure, data, analytics in organizations
    
Pentaho
Published By: AWS     Published Date: Aug 20, 2018
A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
Tags : 
    
AWS
Published By: AWS     Published Date: Jan 03, 2019
Managing your data can be a challenge, but establishing an analytics solution that every user can navigate, regardless of skillset, is where organizations often need help. TIBCO® Spotfire® features AI-driven data visualizations and dashboards, which helps enables each organizational role to discover and deliver valuable insights with ease. Riteway Sales and Marketing, which helps many Southeastern supermarkets execute strategies, leveraged the power of TIBCO Spotfire to better understand individual product performance throughout their stores, achieving exponentially faster time to insight than their previous solution allowed. Watch this on-demand webinar to learn how TIBCO Spotfire, when leveraged on Amazon Web Services cloud, can help you generate deep insights in minutes. You’ll learn: • How to generate relevant, actionable insights from any data, anywhere • Some of the best practices for leveraging AI-driven visual and predictive analytics solutions in the cloud • How to
Tags : 
    
AWS
Published By: AWS     Published Date: Nov 15, 2018
Today’s IT teams spend far too much time struggling against increasing system complexity and tools failing to make monitoring easier and more reliable. To combat these challenges, both admins and site reliability engineers need a clear view of infrastructure performance and availability. Splunk® Insights for Infrastructure (SII) is an analytics-driven monitoring solution that provides the seamless experience organizations need for infrastructure monitoring on the AWS cloud. Download this product brief and discover how SII offers: • An easy install within minutes—available as a free download • Detailed investigations through granular metrics • Seamless monitoring and troubleshooting
Tags : 
    
AWS
Published By: CA Technologies EMEA     Published Date: May 25, 2018
Software drives competitive advantage more than ever at an increasing velocity for releases along with higher, overwhelming levels of deployment complexity. Dramatic growth in mobile applications, analytics, systems of engagement, and cloud demands that organizations respond adaptively, even as resource constraints make it challenging to nearly impossible to do so. As a result of these combined factors, IDC sees increased interest in, demand for, and adoption of agile approaches to development and also for business initiatives driving adoption of agile approaches to overall project, program, and portfolio management.
Tags : 
idc, marketscape, agile, ppm, vendor, assessment
    
CA Technologies EMEA
Published By: AWS - ROI DNA     Published Date: Nov 19, 2018
Today’s IT teams spend far too much time struggling against increasing system complexity and tools failing to make monitoring easier and more reliable. To combat these challenges, both admins and site reliability engineers need a clear view of infrastructure performance and availability. Splunk® Insights for Infrastructure (SII) is an analytics-driven monitoring solution that provides the seamless experience organizations need for infrastructure monitoring on the AWS cloud. Download this product brief and discover how SII offers: • An easy install within minutes—available as a free download • Detailed investigations through granular metrics • Seamless monitoring and troubleshooting
Tags : 
    
AWS - ROI DNA
Published By: Pure Storage     Published Date: Dec 05, 2018
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Read this MIT Technology Review custom paper to learn how advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics, helping to accelerate business outcomes for data driven organizations.
Tags : 
    
Pure Storage
Published By: Pure Storage     Published Date: Dec 05, 2018
Data is the new currency. Is your organization capitalizing on the full potential of data analytics? In this big data primer, you will learn about the 3 key challenges facing organizations today: managing overwhelming amounts of data, leveraging new complex tools/technologies, and developing the necessary skills and infrastructure. And since storage is where your organization's data lives, it’s a pivotal part of the infrastructure jigsaw puzzle. Thus with a “tuned for everything” storage solution that is purpose-built for modern analytics, you can confidently harness the power of your data to drive your enterprise forward.
Tags : 
    
Pure Storage
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set: • Enterprise-class relational database query and management system • Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools • Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
Tags : 
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technolog
Tags : 
    
Amazon Web Services
Published By: McAfee     Published Date: Nov 20, 2014
This paper is the result of a recent SANS survey exploring the use of analytics and intelligence today and exposes the impediments to successful implementation. Organizations that are deploying analytics and intelligence properly are experiencing faster response and detection times, as well as greater visibility. However, many are confused about how to integrate and automate their intelligence collection processes.
Tags : 
siem, threat intelligence, platform integration, correlation and analysis, third-party intelligence tools
    
McAfee
Published By: AWS     Published Date: Jun 20, 2018
Data and analytics have become an indispensable part of gaining and keeping a competitive edge. But many legacy data warehouses introduce a new challenge for organizations trying to manage large data sets: only a fraction of their data is ever made available for analysis. We call this the “dark data” problem: companies know there is value in the data they collected, but their existing data warehouse is too complex, too slow, and just too expensive to use. A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated q
Tags : 
    
AWS
Published By: Anaplan     Published Date: Nov 27, 2017
"The pressure on sales to meet and exceed ever-increasing revenue targets is higher than ever before. At the heart of this challenge lies a complex analytical and modeling problem that involves data spread across many rigid–and usually disconnected–systems, teams, and geographies. Leading companies handle this problem by focusing first on creating a sales performance plan that is data-driven and tied to business objectives. The research report conducted by Harvard Business Review provides you with how today's sales executives: • Overcome technology weaknesses to uncover sophisticated analytics • Change ingrained, cultural tendances of sales organizations • Adopt dynamic practices to respond to change quicker"
Tags : 
    
Anaplan
Published By: Infosys     Published Date: Dec 03, 2018
Data is a truly inexhaustible resource for an organization. It creates endless possibilities to make data do more. As a technology partner of hundreds of organizations around the world, Infosys helps clients navigate the journey from their current state to the next. Facilitating clients’ transition into data-native enterprises is a crucial part. To understand how companies are using data analytics today and their expectations in a world of endless possibilities with data, we recently commissioned an independent survey of 1,062 senior executives from organizations with annual revenues exceeding US$ 1 billion, in the United States, Europe, Australia, and New Zealand. The respondents were from business and technology roles, who were decision makers, program managers and external consultants; represented 12 industries, grouped into seven industry clusters, such as, consumer goods, retail and logistics, energy and utilities, financial services and insurance, healthcare and life sciences, h
Tags : 
    
Infosys
Published By: Aon Hewitt     Published Date: Aug 02, 2016
As the trend of moving to the Cloud continues to flow from business function to business function, other trends are emerging. As organizations transform to eliminate complex functions, standardize and integrate systems to reduce costs, and minimize nonvalue add activities, they are challenging themselves to get the most from their investment. The shift from transactional to strategic, and from reporting to actionable and predictive analytics, positions companies for growth like never before. Many organizations look to break down silos, not only within their company but also within their industries, to share lessons and leverage efficiencies from others’ learnings. Our recommendation is to start by breaking down any silos that exist between finance, HR, and IT within your organization today—and discover what moving to cloud and truly adopting the SaaS lifestyle can do for your organization.
Tags : 
aon, finance, cloud, human resources
    
Aon Hewitt
Published By: Interactive Intelligence     Published Date: Oct 10, 2012
Read why the emergence of speech analytics will continue to help organizations realize value in this Research Perspective from Ventana Research, sponsored by Interactive Intelligence.
Tags : 
customer experience, customer care, speech analytics
    
Interactive Intelligence
Published By: IBM Software     Published Date: Feb 14, 2011
This white paper explores how predictive analytics helps marketing organizations increase ROI by executing highly targeted campaigns focused on high revenue-generating customers and prospects.
Tags : 
ibm cognos, predictive analytics, marketing campaign management system, roi, customer behaviour
    
IBM Software
Published By: IBM Software     Published Date: Jan 25, 2012
Business analytics is the means by which organizations optimize business outcomes. Using insights that can be accessed, shared and acted on by employees at every level, organizations can increase profits, reduce costs, manage risk and make more accurate predictions to prepare for future outcomes. Learn why analytics-driven organizations outperform their peers.
Tags : 
ibm, cognos, business intelligence, technology, analytics, business analytics
    
IBM Software
Published By: IBM Software     Published Date: Feb 03, 2012
This paper from IBM describes how to build a proactive threat and risk strategy based on predictive analytics; examples of how organizations used predictive analytics to minimize the negative impact of risk and maximize positive results; and steps to advance your organization's use of predictive analytics to combat threat and risk.
Tags : 
predictive threat, security, technology, risk management, security policy, ibm, intrustion protection
    
IBM Software
Published By: SAS     Published Date: Jun 05, 2017
"As more products and machines become connected, and analytical capabilities grow, new applications for the Internet of Things (IoT) will emerge. So too will manufacturers change how they make business decisions. This IndustryWeek Special Research Report gauges the current and planned usage of IoT technology and analytics by US manufacturers. It also explores how manufacturers can develop a specific IoT strategy and apply analytics more widely across their organizations to drive revenue, cut costs and innovate. "
Tags : 
    
SAS
Published By: SAS     Published Date: Oct 18, 2017
With the support of SAS, the Internet of Things Institute developed the 2017 Internet of Things ROI Research Study to gather real-world insights, lessons learned and future guidance from current users of IoT technology and advanced analytics. This selective sample of IoT users offers valuable insights to both IoT innovators and organizations still waiting to see how the technology evolves before investing. Multiple business layers and functions have input into IoT decision making. Discover which layer was most critical to success for those organizations that have achieved the highest percentage of their targeted ROI. Learn about the main drivers of success for IoT users achieving higher returns. Lastly, the results highlight six primary factors that can undermine an IoT initiative and how they can be prevented.
Tags : 
    
SAS
Published By: SAS     Published Date: Aug 06, 2019
Under risk adjustment, health plans with a lower average risk score make payments into the system or miss out on revenue opportunities, while plans with relatively high average risk scores receive payments. So it’s critical for a plan to get this analysis right – or forfeit revenue it deserves. With advanced analytics and machine learning, health care organizations can be more timely and confident in their risk adjustment programs, more effectively managing the cost of care and building a stable annual financial portfolio.
Tags : 
    
SAS
Published By: SAS     Published Date: Aug 06, 2019
With the combination of electronic health records, rich repositories of claims data, medical device outputs, laboratory and prescription systems, real-world data and the data mined from other information technology systems, the health and life sciences ecosystem can now gain new perspective. Download this complimentary paper to learn more about how health care data has the power to transform the sector, helping to address the industry’s biggest challenges surrounding costs and quality of patient care. By adopting solutions that allow them to both produce and consume data analytics insights in a way that better guides clinical and business strategies, innovative health care organizations can learn not only to survive but also thrive in the decades to come.
Tags : 
    
SAS
Published By: SAS     Published Date: Aug 19, 2019
With the combination of electronic health records, rich repositories of claims data, medical device outputs, laboratory and prescription systems, real-world data and the data mined from other information technology systems, the health and life sciences ecosystem can now gain new perspective. Download this complimentary paper to learn more about how health care data has the power to transform the sector, helping to address the industry’s biggest challenges surrounding costs and quality of patient care. By adopting solutions that allow them to both produce and consume data analytics insights in a way that better guides clinical and business strategies, innovative health care organizations can learn not only to survive but also thrive in the decades to come.
Tags : 
    
SAS
Start   Previous    1 2 3 4 5 6 7 8 9    Next    End
Search      

Add Research

Get your company's research in the hands of targeted business professionals.