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analytics strategy

Results 101 - 125 of 142Sort Results By: Published Date | Title | Company Name
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: Apr 23, 2015
With IBM analytics for big data with a smart mobile strategy, banks can increase wallet share and assets under management while lowering the organization’s operating ratio by using more efficient channels.
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ibm, analytics, efficiencies, digital banking, management, strategy, data management, business technology
    
IBM
Published By: IBM     Published Date: Nov 09, 2015
This report will discuss the challenges most companies face with managing their data and suggest some strategies and solutions to turn midmarket data into a working asset.
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ibm, analytics, strategy, data, business technology, data center, research
    
IBM
Published By: IBM     Published Date: Jul 19, 2016
This infographic explains how to build your big data strategy on a solid foundation.
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ibm, analytics, big data, strategy, software development, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Apr 27, 2017
It’s hard to grow your business if you can’t see what’s coming next. What will the demand be for a specific product or service and how should you adjust production? What revenue can be expected and from which channels? Where are the best areas to expand your business? Predictive analytics can provide the answers executives, analysts and business managers need to reduce costs, operate more efficiently and increase the bottom line. Join IBM SPSS and guest Mark Lack, Manager of Strategy Analytics and Business Intelligence with industrial products company Mueller Inc. for a look at how to decrease costs and improve your business’ profitability with predictive analytics. You’ll learn how Mueller extends the value of its Big Data environment by applying predictive techniques to accurately forecast sales, prevent fraud and reduce losses from damaged inventory, saving the company significant time and money.
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predictive analytics, fraud detection, increase revenue, decrease costs, customer retention, hr efficiency, advanced 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: 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: SAS     Published Date: Mar 20, 2019
What’s on the chief data and analytics officer’s agenda? Defining and driving the data and analytics strategy for the entire organization. Ensuring information reliability. Empowering data-driven decisions across all lines of business. Wringing every last bit of value out of the data. And that’s just Monday. The challenges are many, but so are the opportunities. This e-book is full of resources to help you launch successful data analytics projects, improve data prep and go beyond conventional data governance. Read on to help your organization become truly data-driven with best practices from TDWI, see what an open approach to analytics did for Cox Automotive and Cleveland Clinic, and find out how the latest advances in AI are revolutionizing operations at Volvo Trucks and Mack Trucks.
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SAS
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
    
IBM
Published By: IBM     Published Date: Oct 15, 2013
Using analytics and personalized marketing to increase revenue and customer loyalty
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search engine marketing, multichannel retailers, data science, retail marketing, online channels, traditional channels, optimizing marketing efforts, high-value customers
    
IBM
Published By: IBM     Published Date: Jan 09, 2014
According to Dr. Barry Devlin of 9sight Consulting, the truth behind all the talk about big data and the possibilities it can offer is not hard to see, provided that organizations are willing to return to the principles of good data management processes.
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ibm, big data, 9sight consulting, data, it management, maximize business, deployment, business opportunities
    
IBM
Published By: IBM     Published Date: Jan 09, 2014
To operate effectively in different markets, Finnish manufacturer Meka Pro needed to be able to adjust its pricing and manufacturing strategies to each locality, but had no insight into their own data. Read this case study to learn how Meka Pro used IBM® Cognos® software modules to make faster, better business decisions and improve profitability.
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ibm, meka pro, analytics, improve profitability, manufacturing projects, business strategy, competition support, manufacturing strategies
    
IBM
Published By: IBM     Published Date: Oct 14, 2014
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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it trends, data center strategies, cloud computing, mobile technology, it management, data management, business technology
    
IBM
Published By: IBM     Published Date: Jan 05, 2015
This white paper will discuss the challenges most companies face with managing their data and suggest some strategies and solutions to turn midmarket data into a working asset.
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analytics, midmarket organizations, analytic solutions, midmarket data, it management, knowledge management, enterprise applications, data management
    
IBM
Published By: IBM     Published Date: Jan 09, 2015
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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it trends, mobile technology, social collaborition, data analytics, big data, data center strategy, it management, knowledge management
    
IBM
Published By: IBM     Published Date: Apr 07, 2015
Using data to reinvent one’s business has reached the mainstream. Data and analytics allow us to change the world around us: it gives us insights into what is happening, allowing us to optimize our strategy, create new business opportunities, and make more accurate predictions.
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ibm, data management, analytics, insights, optimization strategy, predictions, middleware
    
IBM
Published By: IBM     Published Date: Apr 15, 2015
EMA is very much aligned with the directions that IBM is taking in its IT operations analytics strategy and product portfolio. While there is room for improvement, EMA remains optimistic that Netcool Operations Insight is the next step in a continuing set of leadership moves by the company.
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business intelligence, efficiency, analytics, big data, cloud computing, insight, cloud computing
    
IBM
Published By: IBM     Published Date: Jul 15, 2015
The Forrester Wave.
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big data, analytics solutions, evaluate, analytical data, strategy
    
IBM
Published By: SPSS     Published Date: Jun 30, 2009
This whitepaper makes the case for using predictive analytics as a catalyst for that growth. It includes best practices from several global companies.
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spss, roi, customer interactions, predictive analytics, return on investment, predictive insight, crm, customer relationship management
    
SPSS
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
This whitepaper makes the case for using predictive analytics as a catalyst for that growth. It includes best practices from several global companies.
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spss, roi, customer interactions, predictive analytics, return on investment, predictive insight, crm, customer relationship management
    
SPSS, Inc.
Published By: SAS     Published Date: May 17, 2016
This report provides a guide to some of the opportunities that are available for using machine learning in business, and how to overcome some of the key challenges of incorporating machine learning into an analytics strategy. We will discuss the momentum of machine learning in the current analytics landscape, the growing number of modern applications for machine learning, as well as the organizational and technological challenges businesses face when adopting machine learning. We will also look at how two specific organizations are exploiting the opportunities and overcoming the challenges of machine learning as they’ve embarked on their own analytic evolution.
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oreilly, evolution of analytics, sas, machine learning, analytics landscape, networking, it management, data management
    
SAS
Published By: SAS     Published Date: Jun 05, 2017
Analytics is now an expected part of the bottom line. The irony is that as more companies become adept at analytics, it becomes less of a competitive advantage. Enter machine learning. Recent advances have led to increased interest in adopting this technology as part of a larger, more comprehensive analytics strategy. But incorporating modern machine learning techniques into production data infrastructures is not easy.Businesses are now being forced to look deeper into their data to increase efficiency and competitiveness. Read this report to learn more about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated both organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
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SAS
Published By: IBM     Published Date: Aug 20, 2013
When 83 percent of online consumers participate in social media, it is no surprise that, like bees to honey, marketers are following suit. According to a recent IBM® Unica® survey of marketers, 47 percent of respondents say they currently use social media marketing tactics; in North America, that number jumps to 58 percent. Yet, for all the rush, many marketers are wondering, “where’s the gold?” The IBM Unica survey found that 48 percent of marketers admit that their social media marketing efforts are totally siloed, frustrating their attempts to create richer customer relationships.
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social media, social media analytics, social media marketing, ibm, unica, crm, customer relationship management, top-line marketing strategy
    
IBM
Published By: Riverbed     Published Date: Jul 15, 2014
Your business is complex. Big data promises to manage this complexity to make better decisions. But the technology services that run your business are also complex. Many are too complex to manage easily, fueling more complexity, delays, and downtime. Forrester predicts this will inevitably get worse. To combat this onslaught, you can no longer just accelerate current practices or rely on human intelligence. You need machines to analyze conditions to invoke the appropriate actions. These actions themselves can be automated. To perform adaptive, full-service automation, you need IT analytics, a disruption to your existing monitoring and management strategy.
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big data analysis, it analytics, manage, complex, automation, monitoring, management strategy, networking
    
Riverbed
Published By: FollowAnalytics     Published Date: Jun 26, 2015
Download this whitepaper to understand the importance of creating relevant push messaging that engages rather than alienates your users.
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followanalytics, push marketing, push messaging, messaging, mobile marketing, marketing strategy, social media marketing, social media
    
FollowAnalytics
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