predictive business

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Published By: Splunk     Published Date: Aug 17, 2018
Imagine a world where incident alerts arrive 30 minutes before problems even begin — you’d actually have the power to prevent outages and deliver a truly seamless experience to your customers. Sound impossible? Think again — the right AIOps (Artificial Intelligence for IT Operations) solution can help you maintain uptime, reduce manual incident-management tasks and increase productivity.
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it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
    
Splunk
Published By: Splunk     Published Date: Aug 17, 2018
IT organizations are now responsible for delivering seamless customer experiences while preventing outages and managing an increasing number of systems. With growing responsibility placed on IT, there is an opportunity to drive strategy for company-wide business processes and operations. Companies using machine data powered platforms like Splunk collect disparate data types to quickly troubleshoot and monitor systems. By adding predictive capabilities, IT can glean critical insights for the business and develop strategic initiatives on issues that matter. Download the white paper “Embracing the Strategic Opportunity of IT” to learn how to: Enable a business aware IT organization Unlock operational efficiencies Solve problems with predictive analytics
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it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
    
Splunk
Published By: Splunk     Published Date: Aug 22, 2018
The world of artificial intelligence (AI) has finally arrived at the doorstep of IT operations. As organizations move toward using both big data and machine learning functionality to support a variety of IT operations, processes and tasks, artificial intelligence for IT operations (AIOps) platforms have emerged as a one-stop solution. Gartner has released a “Market Guide for AIOps Platforms” that provides findings about the AIOps industry and its latest developments. Download your complimentary copy to: *Gain insight into the developing industry of AIOps and its future *Learn how to optimize IT operations powered by machine learning to drive business value *Compare different AIOps platform vendors and their range of capabilities
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it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
    
Splunk
Published By: Dun & Bradstreet     Published Date: Oct 21, 2016
It is important to understand the different business situations where traditional predictive analytics can be best applied and where anticipatory analytics may be a more appropriate approach to solve the business problem. One is not necessarily superior to the other – it’s about which methodology is best utilized in solving the specific business problem. Conventional response modeling, revenue potential modeling, wallet share analysis, traditional risk scoring and other analytic practices will always be important tools for businesses far-and-wide, but as more companies focus on analytics to inform growth, they’ll have employ the right team and identify the right partners to work with in order to successfully leverage anticipatory analytics to gain a competitive advantage. Looking forward, we anticipate anticipatory analytics playing an important role in your future. Download this white paper to learn more.
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Dun & Bradstreet
Published By: IBM     Published Date: Jun 16, 2015
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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data center, predictive analytics, data center strategy, resilient infrastructure, cloud computing, social collaboration, business analytics, emerging technologies, virtualization, automation, infrastructure, mobile computing, mobile data systems, best practices, business activity monitoring, business process automation, enterprise software, server virtualization, collaboration, employee performance
    
IBM
Published By: Splunk     Published Date: Sep 10, 2018
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable. Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
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it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
    
Splunk
Published By: Splunk     Published Date: Dec 11, 2018
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences. Download this executive brief from CIO to learn: 5 steps to an effective predictive IT strategy Where AI can help, and where it can’t How to drive revenue and exceptional customer experiences with predictive analytics
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk
Published By: iKnowtion     Published Date: Sep 14, 2010
The terms "customer segmentation" and "customer predictive modeling" are often used interchangeably, however, they're very different and support different business objectives. This paper explains why both are required to effectively compete in today's customer-centric marketing landscape.
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crm strategies, customer intelligence, marketing analytics, customer development, marketing effectiveness, iknowtion, segmentation, modeling, predictive modeling, customer centric, targeted, roi
    
iKnowtion
Published By: IBM     Published Date: Jul 14, 2016
This video describes how data scientists, analysts and business users can save precious time by using a combination of SPSS and Spark to uncover and act on insights in big data.
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ibm, data, analytics, predictive business, ibm spss, apache spark, coding, data science, software development, enterprise applications, data management, data center
    
IBM
Published By: IBM     Published Date: Jul 14, 2016
IBM SPSS Solutions offer a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end.
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ibm, big data, data analytics, ibm spss, predictive business, enterprise applications, data management, data center
    
IBM
Published By: IBM     Published Date: May 03, 2016
In this report you will learn how to enhance your customer relationships across all your channels and touch points, produce personalized customer offers and learn from real-world case studies across various industries.
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ibm, ibm predictive customer intelligence, business analytics, customer relations, business intelligence, customer relationship management
    
IBM
Published By: IBM     Published Date: Jul 14, 2017
Today’s CMO is responsible for selling experiences, not just products. Two-thirds of our respondents regard developing deeper, richer customer experiences as their top marketing priority. Learn how Torchbearer CMOs are meeting these expectations and expanding their roles by putting the entire customer journey first.
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cloud computing, mobile solutions, convergence, technology advances, predictive analysis, business value
    
IBM
Published By: Group M_IBM Q1'18     Published Date: Feb 15, 2018
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
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analytics assessment, business decisions, predictive analytics, analytics
    
Group M_IBM Q1'18
Published By: TIBCO Software     Published Date: Aug 13, 2018
The combination of legislation, market dynamics, and increasingly sophisticated risk management strategies requires you to be proactive in detecting risks like fraud quicker and more effectively. Dynamic detection systems need to adapt to evolving compliance regulations, scale to deal with growing transaction volumes, detect sophisticated risk specific patterns, and reduce false-positives. TIBCO's Risk Management Accelerator uses a combination of predictive analytics, streaming analytics, and business process management to deliver a powerful and cost-effective system for detecting anomalies. Download this solution brief to learn more.
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TIBCO Software
Published By: Domino Data Lab     Published Date: Feb 08, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
Published By: Domino Data Lab     Published Date: Feb 08, 2019
A data science platform is where all data science work takes place and acts as the system of record for predictive models. While a few leading model-driven businesses have made the data science platform an integral part of their enterprise architecture, most companies are still trying to understand what a data science platform is and how it fits into their architecture. Data science is unlike other technical disciplines, and models are not like software or data. Therefore, a data science platform requires a different type of technology platform. This document provides IT leaders with the top 10 questions to ask of data science platforms to ensure the platform handles the uniqueness of data science work.
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Domino Data Lab
Published By: Domino Data Lab     Published Date: May 23, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
Published By: BMC ESM     Published Date: Aug 20, 2009
See the highlights of BMC’s Application Performance and Analytics; a predictive, resourceful and intelligent solution that empowers IT Operations to reduce mean time to repair (MTTR), avoid problems with early warning, find problems faster using fewer resources, ensure applications meet business requirements and put the right person on the right problem, every time.
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bmc, application performance and analytics, it operations, mttr, mean time to repair, data center, enterprise applications, application performance management, performance testing
    
BMC ESM
Published By: SAS     Published Date: Apr 21, 2015
Exploring predictive analytics for the first time? Malene Haxholdt, global marketing manager for business analytics at SAS, explains what you need to know to get started.
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SAS
Published By: Epicor     Published Date: Jan 09, 2018
Successful financial management really comes down to providing employees with the tools they need to make the most informed decisions at any given time. Accurate forecasts, budgets, and plans lead to smarter investments. In this Aberdeen research report, top performers are found to provide their employees with the tools that enable success, in addition to exhibiting the following characteristics: • Predictive • Informed • Efficient • Agile Download the report to find out how Epicor enterprise resource planning (ERP) solutions can help you improve your processes and turn your manufacturing business into a financial planning, budgeting, and forecasting leader.
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enterprise resource planning (erp), financial management, manufacturing, budgeting, forecasting
    
Epicor
Published By: BlackLine     Published Date: Aug 06, 2018
The capacity to be anticipatory (aware, predictive and adaptive) of emerging technology and trends in business, demographics, and the social environment impacting your organization and industry. It is crucial to be #FutureReady
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BlackLine
Published By: Alteryx, Inc.     Published Date: Sep 06, 2017
Predictive analytics is on the verge of widespread adoption as enterprises become more interested in deploying predictive capabilities. In fact, a recent 2017 TDWI education survey, ranked predictive analytics the top analytics-related topic respondents wanted to learn about. The TDWI Navigator Report- Predictive Analytics provides a comprehensive overview of the state of the predictive analytics market. Download this report to better understand: Opportunities and obstacles of implementing predictive analytics Market forces and trends driving the adoption of predictive analytics Features and market landscapes that define predictive analytics Download this report today to get a better sense on how your organization can take advantage of predictive analytics to drive change in your business.
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Alteryx, Inc.
Published By: Microsoft     Published Date: May 16, 2016
Each predictive maintenance project will be unique—tailored to the needs of your business and your equipment. But at its core, the principles and considerations for a predictive maintenance solution are very similar. Download this whitepaper for a framework for getting started with your predictive maintenance projects.
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iot, internet of things, microsoft, predictive maintenance project, predictive maintenance solution, devices, return on investment
    
Microsoft
Published By: IBM Software     Published Date: Nov 02, 2010
This paper describes five practical steps companies can take to achieve customer intimacy and, by doing so, provide a springboard for excellence in the other critical value disciplines.
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ibm cognos predictive analysis, business performance, customer relationship, customer intimacy, application performance management, customer interaction service, customer relationship management, customer satisfaction, customer service, ebusiness
    
IBM Software
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