it operations analytics

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Published By: SAS     Published Date: Jun 11, 2018
Electric vehicle technology touches all areas of the utility business, including IT, forecasters and grid operations. The growth of IoT-connected devices, both in the utility-owned grid and customer-owned smart energy apps, makes this a rich field for innovation. But what analytics infrastructure is needed in order to manage the future demand coming from EVs? And what opportunities and risks do EVs present? This white paper from Navigant Research, sponsored by SAS and Intel, explores the analytics infrastructure that utilities need to prepare for and benefit from the growth of EVs.
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SAS
Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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Group M_IBM Q418
Published By: SAS     Published Date: Aug 28, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
Published By: IBM     Published Date: Apr 10, 2013
Your goal is clear—produce high-quality goods while optimizing resources at every step of production. And in today's uncertain economy, cost-control efforts may never have been more important. Unscheduled downtime because of equipment failure can have a serious impact on your organization's bottom line. Download this white paper from IBM, and learn the basics of predictive maintenance, the benefits it provides manufacturing operations and the underlying technologies that make it possible. Predictive analytics helps you in a number of ways: identify when equipment is likely to fail or need maintenance and take action to maximize up time and reduce future warranty claims costs; optimize allocated labor resources and spare part inventories, helping eliminate undue maintenance, prevent downtime and reduce inventory costs; and determine why certain production runs fail more often than others, identify the cause and analyze whether those runs warrant a recall.
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predictive, maintenance, manufacturing, productivity, minimize, downtime, reduce, cost-control
    
IBM
Published By: IBM     Published Date: Jul 22, 2014
Listen to an interactive discussion (socialcast) with a select group of IBM Data Scientists that goes beyond the tools and tackles new ways your business can use data.
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ibm, it operations analytics, it operations, analytical applications, data, big data, it app infrastructure, cloud, data science, ibm software, it management
    
IBM
Published By: IBM     Published Date: Nov 06, 2014
In this webcast, you’ll learn how IBM® SmartCloud® Analytics—Predictive Insights helps you prevent application degradation and service outages.
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operations analytics, it analytics, service outage prevention, monitoring management solutions, 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
    
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
    
IBM
Published By: IBM     Published Date: Apr 15, 2015
Technology Adoption Analyst whitepaper by Forrester. This IBM-commissioned profile of IT operations decision-makers at enterprise companies in the US, UK and Germany evaluates IT operations analytics adoption, benefits, and challenges based on Forrester’s own market data and a custom study of the same audience.
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ibm, it operations, decision makers, analytics, market analysis
    
IBM
Published By: SAS     Published Date: Oct 18, 2017
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
Published By: Riverbed     Published Date: Sep 05, 2014
As enterprises have embraced IT trends like cloud computing and virtualization, their operational needs have evolved to make application performance more important than ever before. But operating applications at peak performance is challenging in the cloud. That's why many enterprise IT departments now have Applications Operations groups tasked with ensuring that applications run efficiently across these complex IT stacks. But, most tools designed to address these application performance management (APM) issues were never designed for this dynamic environment. To achieve smooth delivery of applications at all times, Applications Operations groups need APM solutions that can give them insight and analytics to manage their apps. This SlashGuide gives IT managers a scorecard to identify APM solutions that will deliver more efficient application performance.
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apm, applications, operations, enterprise, stacks, dynamic
    
Riverbed
Published By: IBM     Published Date: Feb 04, 2015
Is it easy to do business with your organization? Do your employees feel empowered to meet your customer’s needs? These are questions that you’re probably grappling with as you face a perpetually changing business environment. You strive for operational excellence and need ways to effectively acquire and retain new customers. You also need to reinvent your business operations to foster growth. Smarter Process is a way for you to work smarter as you find your way through all the operational challenges that the current business climate throws at you. It helps you use mobile, analytics, and collaboration to empower your employees to do their best work. It also empowers you as a leader to find the right tools and solutions.
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ibm smarter process, customer retention, customer-centric operations, operational decision management, knowledge management
    
IBM
Published By: IBM Software     Published Date: Oct 04, 2011
Changes in market conditions and economic uncertainty have forced consumers to make tradeoffs and alter their spending and shopping habits. As a result, more than ever, retailers have to stay on top of trends and better manage their customer relationships, operations and financial performance to maximize profits. Read these customer success stories to learn how four retailers are optimizing their businesses today with business analytics.
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ibm, customer success, analytics, business, technology, profits
    
IBM Software
Published By: ExtraHop     Published Date: Aug 19, 2013
This white paper explains how IT organizations can harness the wealth of wire data flowing through their environments for real-time IT operational intelligence. Read how companies across a wide range of industries are analyzing wire data for more agile and proactive IT operations.
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extrahop, operations, technology, wire data, intel, networking, knowledge management, business technology
    
ExtraHop
Published By: HP     Published Date: Apr 13, 2014
With growth in the volume and variety of data needed to monitor and manage complex IT systems, IT leaders have had to acquire new technologies to manage this data. This will require that a single, architected platform be procured to improve root-cause analysis and short-term predictive analysis.
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ops analytics, operations analytics, gartner, big data, analytics, predictive analytics, bsm, business service management, data management
    
HP
Published By: HP     Published Date: Apr 23, 2014
With growth in the volume and variety of data needed to monitor and manage complex IT systems, IT leaders have had to acquire new technologies to manage this data. This will require that a single, architected platform be procured to improve root-cause analysis and short-term predictive analysis.
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ops analytics, operations analytics, gartner, big data, analytics, predictive analytics, bsm, business service management, data management
    
HP
Published By: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
"Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect."
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
"Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect."
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Hewlett Packard Enterprise
Published By: IBM     Published Date: Jun 07, 2017
Read this eBook to get insight on the essential elements of a modernized B2B integration architecture. Companies need a strategy as they think about modernizing their B2B integration capabilities. This eBook describes what to look for and how IBM can help. You’ll learn about: · Operating a single, secure B2B integration gateway · Simplified onboarding and partner management. · High availability business operations and disaster recovery · Adaptable capabilities to help react to changes to your business processes · Visibility and analytics that provide actionable insight over those processes · Supporting a mix of hybrid deployment models including on-premises and cloud
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b2bi, ibm, b2b integration, modernization, b2b architechture
    
IBM
Published By: IBM     Published Date: Oct 16, 2017
This white paper examines how some of the ways organizations use big data make their infrastructures vulnerable to attack. It presents recommended best practices organizations can adopt to help make their infrastructures and operations more secure. And it discusses how adding advanced security software solutions from IBM to their big-data environment can fill gaps that big-data platforms by themselves do not address. It describes how IBM® Security Guardium®, an end-to- end solution for regulatory compliance and comprehensive data security, supports entitlement reporting; user-access and activity monitoring; advanced risk analytics and real-time threat detection analytics; alerting, blocking, encryption and other data protection capabilities, as well as automated compliance workflows and reporting capabilities, to stop threats.
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security, big data, ibm, data protection
    
IBM
Published By: Box     Published Date: Jun 22, 2018
• There are many opportunities for businesses to introduce the concept of paper-free or less intensive paper processes to their organizations. AIIM 2016 Industry Watch research found that “58% of respondents described their inbound handling of content as ad-hoc”. This is not surprising given paper is still fairly dominant in many businesses due to human desire to keep paper in hand for reading, note taking, and still today, signatures. • In this study we take a look the challenges businesses face in relation to: o Digital Transformation of their business operations o Capturing and managing multi-channel inbound content, including paper o Steps taken to automate the information capture process o Use of analytics to enhance the identification and classification of capture information o A look ahead at the next 5 years to understand where businesses are focusing their efforts and funding
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Box
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