business analytics

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By: IBM     Published Date: Sep 02, 2014
Advanced analytics strategies yield the greatest benefits in terms of improving patient and business outcomes when applied across the entire healthcare ecosystem. But the challenge of collaborating across organizational boundaries in order to share information and insights is daunting to many stakeholders. In this worldwide survey of 555 healthcare providers, payers and life sciences organizations, you will learn the importance of implementing collaborative analytics strategies that: Manage, integrate and interpret data generated at all stages of the healthcare value chain Achieve the right balance of skills in order to translate data into actionable insights Focus on executive sponsorship and enterprise-wide adoption with metrics to measure and track success Position yourself to harness data, create and share insights, make informed decisions, and improve the performance of the entire healthcare ecosystem in which you operate.
Tags : ibm, analytics acrosss ecosystem
     IBM
By: IBM     Published Date: Sep 02, 2014
In today’s stringent financial services regulatory environment with exponential growth of data and dynamic business requirements, Risk Analytics has become integral to businesses. IBM Algorithmics provides very sophisticated analyses for a wide range of economic scenarios that better quantify risk for multiple departments within a firm, or across the enterprise. With Algorithmics, firms have a better handle on their financial exposure and credit risks before they finalize real-time transactions. But this requires the performance and agility of a scalable infrastructure; driving up IT risk and complexity. The IBM Application Ready Solution for Algorithmics provides an agile, reliable and high-performance infrastructure to deliver trusted risk insights for sustained growth and profitability. This integrated offering with a validated reference architecture delivers the right risk insights at the right time while lowering the total cost of ownership.
Tags : ibm, it risk, financial risk analytics
     IBM
By: IBM     Published Date: May 20, 2015
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     IBM
By: IBM     Published Date: May 20, 2015
According to our global study of more than 800 cloud decision makers and users are becoming increasingly focused on the business value cloud provides. Cloud is integral to mobile, social and analytics initiatives – and the big data management challenge that often comes with them and it helps power the entire suite of game-changing technologies. Enterprises can aim higher when these deployments are riding on the cloud. Mobile, analytics and social implementations can be bigger, bolder and drive greater impact when backed by scalable infrastructure. In addition to scale, cloud can provide integration, gluing the individual technologies into more cohesive solutions. Learn how companies are gaining a competitive advanatge with cloud computing.
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     IBM
By: IBM     Published Date: Sep 16, 2015
The impact of the 2008 financial crisis affects not only Sell Side firms - the focus of discussions - but Buy Side and Insurance firms. Dodd Frank Act targets all systemically important firms. This study conducted in partnership with Waters Technology, an Incisive Media publication, focuses these firms. The report finds that they are facing intense pressure on multiple fronts including stricter liquidity and solvency risk regulations, and changing market conditions. Like Sell Side firms, they require more innovative business models and analytics to meet these challenges and to deliver growth and performance.
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     IBM
By: Impetus     Published Date: Mar 15, 2016
Streaming analytics platforms provide businesses a method for extracting strategic value from data-in-motion in a manner similar to how traditional analytics tools operate on data-at rest. Instead of historical analysis, the goal with streaming analytics is to enable near real-time decision making by letting companies inspect, correlate and analyze data even as it flows into applications and databases from numerous different sources. Streaming analytics allows companies to do event processing against massive volumes of data streaming into the enterprise at high velocity.
Tags : impetus, guide to stream analytics, real time streaming analytics, streaming analytics, real time analytics, big data analytics
     Impetus
By: TIBCO     Published Date: Sep 02, 2014
In this Guide you will learn how predictive analytics helps your organization predict with confidence what will happen next so that you can make smarter decisions and improve business outcomes. It is important to adopt a predictive analytics solution that meets the specific needs of different users and skill sets from beginners, to experienced analysts, to data scientists.
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     TIBCO
By: IBM     Published Date: Nov 14, 2014
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     IBM
By: Revolution Analytics     Published Date: May 09, 2014
As the primary facilitator of data science and big data, machine learning has garnered much interest by a broad range of industries as a way to increase value of enterprise data assets. Through techniques of supervised and unsupervised statistical learning, organizations can make important predictions and discover previously unknown knowledge to provide actionable business intelligence. In this guide, we’ll examine the principles underlying machine learning based on the R statistical environment. We’ll explore machine learning with R from the open source R perspective as well as the more robust commercial perspective using Revolution Analytics Enterprise (RRE) for big data deployments.
Tags : revolution analytics, data science, big data, machine learning
     Revolution Analytics
By: Adaptive Computing     Published Date: Feb 27, 2014
Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers. Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.
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     Adaptive Computing
By: Hewlett Packard Enterprise     Published Date: Jul 25, 2019
With digital IT transformation solutions and new business models driven by the democratization of data, advanced analytics, and a citizen-centric approach, HPE helps cities like yours get smarter—and continue to evolve into great places for your citizens to live. Visit hpe.com/info/public-sector to learn how you can take the next step on your journey.
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     Hewlett Packard Enterprise
By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
Tags : aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state
     Aberdeen
By: KPMG     Published Date: Jul 31, 2019
From intelligent automation to advanced analytics, disruptive technology will enable the finance function to provide all of its services more effectively and efficiently. Find out how technology will change the way finance delivers transactional services, expert services and business partnering, Read this report to discover: • how automation in finance can deliver expert services more reliably and with smaller workforces • how to design an agile workforce of humans and technologies • how the finance function will shift to be part of a cross-functional analytics model that provides key insights to the business
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     KPMG
By: Cisco Umbrella EMEA     Published Date: Sep 02, 2019
"We live and surf in a cyber world where attacks like APT, DDOS, Trojans and Ransomware are common and easy to execute. Domain names are an integral part of any business today and apparently an integral part of an attacker's plan too. Domain names are carriers of malwares, they act as Command and Control servers and malware's ex-filtrate data too. In today's threat landscape - predicting threats, spotting threats and mitigating them is super crucial.. This is called Visibility and Analytics. Watch this on demand session with our Cisco cloud security experts Shyam Ramaswamy and Fernando Ferrari as they talk about how Cisco Umbrella and The Umbrella Research team detect anomalies, block threats and identify compromised hosts. The experts also discuss how effectively Cisco spot, react, filter out IOC, block the network communications of a malware; identify and stop a phishing campaign (unknown ones too). "
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     Cisco Umbrella EMEA
By: Group M_IBM Q4'19     Published Date: Sep 26, 2019
IBM has been named a Leader in Gartner's Magic Quadrant for Data & Analytics Services. According to the report, by 2022, 90% of corporate strategies are expected to view information as a critical enterprise asset, and analytics as an essential competency. Data and analytics service providers can help leaders accelerate and transform their ability to deliver data-driven insights and innovation solutions to businesses. Get complimentary access to Gartner's latest Magic Quadrant report for Data & Analytics Service Providers.
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     Group M_IBM Q4'19
By: Infinidat EMEA     Published Date: Jun 10, 2019
Digital disruption, economic instability, political upheavals and skills shortages have all at some point in the past 24 months been blamed for business failure, or at the very least, lost profitability and earnings. It’s perhaps not a huge surprise that a Gartner CEO survey on business priorities revealed that digital business is a top priority for next year. Survey respondents were asked whether they have a management initiative or transformation program to make their business more digital. The majority (62 percent) said they did. Of those organisations, 54 percent said that their digital business objective is transformational while 46 percent said the objective of the initiative is optimisation.* So, for businesses it’s a case of learning to evolve and be agile, to use technology to help compete more efficiently and not fall victim to inertia. As businesses become increasingly dependent on the insights from data analytics and face-up to competition fuelled by the 24/7 society of in
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     Infinidat EMEA
By: SAS     Published Date: Sep 05, 2019
Organizations are charging ahead with investments in cloud and analytics to deliver agility, scalability and cost savings. With computing power advancements and continuous growth of data, cloud provides the elastic workloads and flexibility required for modern business. However, the environment of flexibility and choice that cloud provides also creates complexity and challenges. In this white paper, learn how organizations are applying expertise and using the latest methods to move analytics to the cloud, including: • Why are organizations moving analytic work to the cloud? • What are the key challenges and misconceptions? • How do IT leaders provide choice while maintaining control?
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     SAS
By: SAS     Published Date: Sep 05, 2019
Envision this situation at a growing bank. Its competitive landscape demands an agile response to evolving customer needs. Fortunately, analytically minded professionals in different divisions are seeing results that positively affect the bottom line. • A data scientist in the business development team analyzes data to create customized • experiences for premium customers. • A digital marketer tracks and influences the customer journey for prospective • mortgage customers. • A risk analyst builds risk models for the bank’s loan portfolios. • A data analyst examines data about local customers. • A technical architect defines a new system to protect bank data from internal and • external cyberthreats. • An application developer builds a new mobile app for online customer portfolio • management. Between them, these employees might be using more than a dozen packages for analytics and data management.
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     SAS
By: Workday     Published Date: Feb 20, 2018
How can you put the power of real-time analytics into the hands of business users? Watch this video to learn about the technologies surrounding self-service analytics and data integration, and how you can use them to lead a data-driven organization.
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     Workday
By: AWS     Published Date: Oct 07, 2019
Hear from speakers: Danielle Greshock, Sr. Manager, Amazon Web Services, Inc. (AWS) Vincent Lam, Head of Cloud Product Marketing, Talend Andy McPhee, Data & Analytics Engineering Director, AstraZeneca
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     AWS
By: Adobe     Published Date: Sep 23, 2019
Why data-driven businesses stand out from the crowd. Why Should the Target Audience Care? Enterprises need to become more data-driven by using more mature analytics tools to stand out from the crowd Supporting Concepts Smart, effective customer analytics tools helps organizations reap the rewards of increased customer satisfaction and brand loyalty. Neglecting advances in customer analytics technology could seriously impact a company's ability to compete in the future marketplace. Where do your customers and prospects sit on the customer analyticsmaturity scale? Are they leaders or are they laggards? Read "Customer Analytics: The 20 Attributes that Lead to Business Success" for insights into: • the key drivers needed within an organisation that help grow customer analytics maturity • why companies using paid analytics solutions experience more tangible benefits than those using free analytics • how to distinguish customer analytics leaders from laggards
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     Adobe
By: Adobe     Published Date: Sep 23, 2019
Like the oxygen we breathe, journey analytics brings life to the customer behind those devices, over time getting to know their favorite pastry choice, when they’re most likely to buy gas, and how long they stay online while in the station’s café. WHY SHOULD THE TARGET AUDIENCE CARE? Business struggle to gain a holistic customer view — the skills to identify actionable insights from multichannel data are in short supply. If they could gain a holistic view of customer attributes and behaviors, they could make sure they get the right content at the right time. SUPPORTING CONCEPTS If you want your customers to enjoy seamless, personalized experiences, you need to treat them like people. That means marketing to the person — not the device. When you know a customer’s interests, wants, and needs — perhaps even before they do — you’ve succeeded at becoming a true experience business. For some, this may require a shift from analytics as a tool to analytics as a way of life. It may also m
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     Adobe
By: SAP     Published Date: Feb 05, 2011
Learn how best-in-class companies access information faster to improve key business performance metrics.
Tags : business performance, sap, real time analytics, business intelligence, analytics
     SAP
By: SAP     Published Date: Jun 18, 2011
To stay ahead of the competition in a global marketplace, firms are increasingly speeding up operations, in many cases adopting real-time systems and tools to allow for instant decision-making and faster business cycles. Download here to learn how.
Tags : real-time business analytics, faster decision making, business automation, business metrics, analytical data, sap
     SAP
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
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