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Published By: IBM     Published Date: Apr 15, 2016
This report examines the current state of self-service analytics across all industries and company sizes. It also highlights the technology decisions and analytical performance of organizations that reported high levels of self-service in their analytical use base.
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ibm, analytics, self-service analytics, business analytics, analytical performance
    
IBM
Published By: IBM     Published Date: Jul 01, 2015
This white paper discusses how organizations can benefit from implementing collaboration and analytics processes in the three core areas
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healthcare analytics, analytics technology, quality assurance, wellness monitoring, performance analysis, patient self-management, information technology, quality and safety, care coordination, meaningful use, enterprise content management
    
IBM
Published By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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SAS
Published By: SAS     Published Date: Jun 06, 2018
A multitude of “things” generate floods of big data – cars, wearables, machines and appliances. Wouldn’t you like to sift through that noise and become an organization that relies on data to make fact-based decisions? Learn about the three foundations of becoming data-driven – data management, analytics and visualization – and how they can increase profitability, boost performance, raise market share and improve operations. Read about hurdles to becoming a data-driven organization and learn best practices from others. Then get a glimpse of what the future holds with the Internet of Things (IoT), edge analytics, artificial intelligence (AI) and other technology innovations.
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SAS
Published By: SAS     Published Date: Mar 14, 2014
The solution to operationalizing analytic s involves the effective combination of a Decision Management approach with a robust, modern analytic technology platform. This paper discusses both how to use a focus on decisions to ensure the right problem gets solved and what such an analytic technology platform looks like.
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sas, predictive analytics, technology platform, solution, operationalizing, production systems
    
SAS
Published By: IBM     Published Date: Apr 29, 2014
Social media is reshaping the relationships that customers have with products, services and brands. Read this white paper to learn how the right combination of technologies can help you understand emerging consumer trends and increase the ROI of your marketing campaigns.
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ibm, retail, social media, social media analytics, consumer insights, customer relationships, roi, business technology, consumer trends, marketing
    
IBM
Published By: Adobe     Published Date: Jan 12, 2015
Download our Field guide to marketing analytics to identify the defining characteristics of mature marketing analytics practices and to learn how your program can join their ranks. You’ll discover four steps to analytics maturity, from benchmarking your current performance to creating a long-term competitive advantage. And you’ll learn how the right marketing analytics can transform your business results.
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adobe, digital, marketing, analytics, benchmarks, competitive, advantage, personalize, experience, customer, channel, mobile, social, search, brand, experience, resources, technology, goals, playbook
    
Adobe
Published By: IBM     Published Date: Oct 13, 2015
This IDC iView will share results of a recent IDC study and provide insights you can use to better understand how advanced analytics strategies can help you enhance the experience for your audience, grow your viewers and advertisers, and increase revenues.
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ibm, audience analytics, idc iview, research, strategy, technology
    
IBM
Published By: IBM     Published Date: Dec 10, 2015
Ovum has produced this Ovum Decision Matrix to identify how the leading customer analytics vendors stack up against each other in terms of their technology, execution of strategy, and market impact.
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IBM
Published By: IBM     Published Date: Jan 21, 2016
Take this assessment, designed specifically for communication service providers, to find out how effective your organization is at harnessing the power of big data and analytics to drive excellence across your organization.
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ibm, telecommunications, analytics, marketing, business technology, internet marketing, crm & customer care, telecom
    
IBM
Published By: IBM     Published Date: Aug 06, 2014
Social media is reshaping the relationships that customers have with products, services and brands. Read this white paper to learn how the right combination of technologies can help you understand emerging consumer trends and increase the ROI of your marketing campaigns.
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ibm, retail, social media, analytics, insights, actionable, relationships, technology
    
IBM
Published By: IBM     Published Date: Oct 06, 2015
This paper explores the implications of cloud, big data and analytics, mobile, social business and the evolving IT security landscape on data center and enterprise networks and the changes that organizations will need to make in order to capitalize on these technology force.
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networks, ibm, redefining networks, cloud, analytics, mobile, social, security, big data, it security, data center, enterprise networks
    
IBM
Published By: IBM     Published Date: Feb 29, 2016
This paper explores the implications of cloud, big data and analytics, mobile, social business and the evolving IT security landscape on data center and enterprise networks and the changes that organizations will need to make in order to capitalize on these technology force.
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ibm, network, cloud, analytics, mobile, social, big data, it security
    
IBM
Published By: Cisco     Published Date: Jul 11, 2016
Companies rely on an expanding set of applications to compete in today's rapidly evolving business environment: - They rely on a fast-growing array of applications and devices (email, collaboration tools, and smartphones/tablets) to communicate and conduct business with customers and business partners. - They are creating, collecting, and repurposing large, unstructured data sets in life sciences, geophysics, media, and manufacturing. - They are collecting, storing, and analyzing more social and sensor-generated data about environments, products, customers, and transactions. The promise of better and faster data-driven decision making based on all this information is pushing big data and analytics (BDA) technology to the top of executive agendas. To succeed, CIOs must place a laserlike investment focus on datacenter solutions that allow them to deliver scalable, reliable, and flexible infrastructure for fast-growing BDA environments. Read more to learn how!
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Cisco
Published By: Cisco     Published Date: Jul 11, 2016
Today's datacenter networks must better adapt to and accommodate business-critical application workloads. Datacenters will have to increasingly adapt to virtualized workloads and to the ongoing enterprise transition to private and hybrid clouds. Pressure will mount on datacenters not only to provide increased bandwidth for 3rd Platform applications such as cloud and data analytics but also to deliver the agility and dynamism necessary to accommodate shifting traffic patterns (with more east-west traffic associated with server-to-server flows, as opposed to the traditional north-south traffic associated with client/server computing). Private cloud and legacy applications will also drive daunting bandwidth and connectivity requirements. This Technology Spotlight examines the increasing bandwidth requirements in enterprise datacenters, driven by both new and old application workloads, cloud and noncloud in nature. It also looks at how Cisco is meeting the bandwidth challenge posed by 3rd
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Cisco
Published By: IBM     Published Date: Nov 30, 2017
Analyst firm, Enterprise Strategy Group, examines how companies can leverage cloud-based data lakes and self-service analytics for timely business insights that weren’t possible until now. And learn how IBM Cloud Object Storage, as a persistent storage layer, powers analytics and business intelligence solutions on the IBM Cloud. Complete the form to download the analyst paper.
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analytics, technology, digital transformation, data lake, always-on data lake, ibm, cloud-based analytics
    
IBM
Published By: SAS     Published Date: Aug 28, 2018
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever. Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
With the widespread adoption of predictive analytics, organizations have a number of solutions at their fingertips. From machine learning capabilities to open platform architectures, the resources available to innovate with growing amounts of data are vast. In this TDWI Navigator Report for Predictive Analytics, researcher Fern Halper outlines market opportunities, challenges, forces, status and landscape to help organizations adopt technology for managing and using their data. As highlighted in this report, TDWI shares some key differentiators for SAS, including the breadth and depth of functionality when it comes to advanced analytics that supports multiple personas including executives, IT, data scientists and developers.
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SAS
Published By: SAS     Published Date: Jan 04, 2019
How can you open your analytics program to all types of programming languages and all levels of users? And how can you ensure consistency across your models and your resulting actions no matter where they initiate in the company? With today’s analytics technologies, the conversation about open analytics and commerical analytics is no longer an either/or discussion. You can now combine the benefits of SAS and open source analytics technology systems within your organization. As we think about the entire analytics life cycle, it’s important to consider data preparation, deployment, performance, scalability and governance, in addition to algorithms. Within that cycle, there’s a role for open source and commercial analytics. For example, machine learning algorithms can be developed in SAS or Python, then deployed in real-time data streams within SAS Event Stream Processing, while also integrating with open systems through Java and C APIs, RESTful web services, Apache Kafka, HDFS and more.
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SAS
Published By: SAS     Published Date: Jan 30, 2019
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever. Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
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SAS
Published By: IBM     Published Date: Sep 27, 2013
Analytics: The Real-World Use of Big Data - How innovative enterprises in the midmarket extract value from uncertain data This study highlights the phases of the big data journey, the objectives and challenges of midsize organizations taking the journey, and the current state of the technology that they are using to drive results. It also offers a pragmatic course of action for midsize companies to take as they dive into this new era of computing.
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ibm, big data, big data solutions, midmarket businesses, analytics
    
IBM
Published By: IBM     Published Date: Oct 10, 2013
Four technology trends—cloud computing, mobile technology, social collaboration and analytics—are shaping the business and converging on the data center. But few data center strategies are designed with the requisite flexibility, scalability or resiliency to meet the new demands. Read the white paper to learn how a good data center strategy can help you prepare for the rigors and unpredictability of emerging technologies. Find out how IBM’s predictive analytics are helping companies build more accurate, forward-looking data center strategies and how those strategies are leading to more agile, efficient and resilient infrastructures.
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technology trends, pervasive technology, data center, resilient infrastructures, collaboration and analytics, mobile technology, ibm, accurate strategies, cloud computing, scalability
    
IBM
Published By: IBM     Published Date: Jan 02, 2014
Many organizations and agencies would like to improve their debt collection. They are aware that advanced analytics can help them optimize collections to drive down company debt and collection expenditures. However, they perceive that advanced analytics requires massive infrastructure changes, expensive software licenses, analytics expertise, long lead times and major upfront capital expenses.
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ibm, analytic answers, prioritized collections, collection agencies, debt collection, constrained budgets, constrained resources, the cloud, analytics technology, predictive and prescriptive, effective collection, up-to-date insights, trends and patterns, capital expenses, operational changes, data-driven, visual trends, potential opportunities, potential threats, business goals
    
IBM
Published By: IBM     Published Date: Jan 02, 2014
For midsize organizations, business analytics offers the crucial ability to transform data into insight and uncover opportunities for growth and competitive advantage. This Aberdeen Sector Insight explores the impact of business analytics in North American midsize organizations.
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ibm, aberdeen group, mid-market analytics, data into insight, business analytics, technology investment, aberdeen sector insight, opportunities for growth, leveraging analytics, actionable insight, data environments, analytical solution, effective analytics, analytical engagement, process efficiency, data capture, data optimization
    
IBM
Published By: IBM     Published Date: Jan 09, 2014
Watson’s success in the Jeopardy! challenge was inspiring, but the business impact of optimized systems design is just beginning. With smarter analytics solutions optimized on IBM Power Systems, you can put Watson's technology to work and ensure that you
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power 7, big data, watson, decision making, power systems, virtualization, spss collaboration, ibm, ibm power systems, analytics
    
IBM
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