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Published By: IBM     Published Date: Dec 05, 2016
Learn directly from KONE's expert about their recent IoT experience in implementing predictive maintenance (PMQ) and IoT. The session will cover: 1) KONE's business area that the PMQ and IoT solution is supporting, and the metrics used to measure success; 2) KONE's Predictive Maintenance and IoT Platform use case, key personas, savings and benefits realized; and 3) Observations from implementation, including: a) The analytics journey at KONE; b) Organizational change (culture, processes, etc.); c) Measurable maintenance benefits; d) Implementation considerations, learnings, going forward; and e) Future projects and capabilities.
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ibm, leadership, watson, watson iot, predictive maintenance
    
IBM
Published By: AWS     Published Date: May 18, 2018
We’ve become a world of instant information. We carry mobile devices that answer questions in seconds and we track our morning runs from screens on our wrists. News spreads immediately across our social feeds, and traffic alerts direct us away from road closures. As consumers, we have come to expect answers now, in real time. Until recently, businesses that were seeking information about their customers, products, or applications, in real time, were challenged to do so. Streaming data, such as website clickstreams, application logs, and IoT device telemetry, could be ingested but not analyzed in real time for any kind of immediate action. For years, analytics were understood to be a snapshot of the past, but never a window into the present. Reports could show us yesterday’s sales figures, but not what customers are buying right now. Then, along came the cloud. With the emergence of cloud computing, and new technologies leveraging its inherent scalability and agility, streaming data
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AWS
Published By: AWS     Published Date: Sep 04, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics.
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AWS
Published By: AWS     Published Date: Sep 04, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technology
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AWS
Published By: Hewlett Packard Enterprise     Published Date: Aug 10, 2016
Download this asset to learn how running old servers impacts productivity and profitability especially for small business. Sponsored by: HPE and Intel®
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intel, hpe, best practices, profitability, productivity, business management, business analytics, business intelligence
    
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: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
Applications are the engines that drive today’s digital businesses. When the infrastructure that powers those applications is difficult to administer, or fails, businesses and their IT organizations are severely impacted. Traditionally, IT assumed much of the responsibility to ensure availability and performance. In the digital era, however, the industry needs to evolve and reset the requirements on vendors. HPE Nimble Storage has broken away from convention and transformed how storage is managed and supported with the HPE InfoSight predictive analytics platform. HPE engaged ESG to conduct a quantitative survey of the HPE Nimble Storage installed base, as well as non-HPE Nimble Storage customers, to better assess how HPE InfoSight positively impacts customer environments. Both HPE InfoSight telemetry data and ESG’s quantitative survey data show that the benefit delivered to HPE Nimble Storage customers is significant, driving: • 79% lower IT operational expenses. • 73% fewer trouble ti
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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: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
Applications are the engines that drive today’s digital businesses. When the infrastructure that powers those applications is difficult to administer, or fails, businesses and their IT organizations are severely impacted. Traditionally, IT assumed much of the responsibility to ensure availability and performance. In the digital era, however, the industry needs to evolve and reset the requirements on vendors. HPE Nimble Storage has broken away from convention and transformed how storage is managed and supported with the HPE InfoSight predictive analytics platform. HPE engaged ESG to conduct a quantitative survey of the HPE Nimble Storage installed base, as well as non-HPE Nimble Storage customers, to better assess how HPE InfoSight positively impacts customer environments. Both HPE InfoSight telemetry data and ESG’s quantitative survey data show that the benefit delivered to HPE Nimble Storage customers is significant, driving: • 79% lower IT operational expenses. • 73% fewer trouble ti
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Hewlett Packard Enterprise
Published By: Veritas     Published Date: Jan 03, 2019
The digital business continues to evolve. Investments in data analytics projects lead the way while traditional, proprietary infrastructures are being disrupted by cloud, open source and hyperconverged paradigms. These changes are forcing IT leaders to contend with greater workload diversity in the midst of tightening budgets. And while the workload [or] IT landscape is changing, the need for reliable data protection remains as crucial as ever to protect against, data corruption, human error, and malicious threats such as ransomware. Learn how Veritas can help you navigate through these obstacles. Join us to hear experts from ESG and Veritas discuss how the right data protection solution today can prepare you for tomorrow's business demands. You will learn: The key trends that are driving change in the digital business The most common causes of data loss in tomorrow’s multi-cloud data centers How to protect an increasingly diverse environment with minimal operational overhead
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Veritas
Published By: IBM     Published Date: Apr 18, 2017
Companies in all industries can benefit from a master data management program, advises MDM expert Anne Marie Smith. Learn how to enhance yours.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations
    
IBM
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: Dassault Systèmes     Published Date: Jun 19, 2018
This white paper outlines a framework that emphasizes digitization and business transformation and the new opportunities pull processes bring. The mechanism of “Pull” processes—those triggered by an actual event instead of a forecast—is nothing new. It is at the heart of many successful manufacturing strategies. Recent technological advances in digitization, including the harnessing of Big Data analytics, the use of the cloud, Business Process Management (BPM), social media, IIoT, and mobility, have extended the power of Pull beyond Lean manufacturing. In the wake of the current technological innovation wave, it is not uncommon for manufacturers to not know what next step to take. In light of these new developments, this white paper will focus on the mechanism of business transformation enabled by these technologies, which can be attributed to two major forces: the power of Pull and digitization. Nine practical applications are detailed, showing how innovative manufacturers can better
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Dassault Systèmes
Published By: Pure Storage     Published Date: Apr 18, 2018
Apache Spark has become a critical tool for all types of businesses across all industries. It is enabling organizations to leverage the power of analytics to drive innovation and create new business models. The availability of public cloud services, particularly Amazon Web Services, has been an important factor in fueling the growth of Spark. However, IT organizations and Spark users are beginning to run up against limitations in relying on the public cloud—namely control, cost and performance.
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Pure Storage
Published By: Google     Published Date: Dec 03, 2018
The Internet of Things is growing fast: By 2025, IoT devices will transmit an estimated 90 zettabytes of data to their intended targets, according to IDC. Armed with information, businesses can revolutionise everything from fraud detection to customer service. But first, they need an architecture that supports real-time analytics so they can gain actionable insights from their IoT data. Read the complete report sponsored by Google Cloud, and learn how to mitigate key IoT-related challenges.
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Google
Published By: Insight Software     Published Date: Mar 14, 2018
xxxx
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kpi, business, data, analytics, metrics, hubble
    
Insight Software
Published By: Forcepoint     Published Date: Oct 03, 2019
In part two of the Unified Data Protection for a Hybrid IT World webinar series, we take a deeper dive into use cases around the challenges that businesses are facing today and how Forcepoint’s solutions meet your data protection needs. Understanding the location of all data, whether at-rest, in-use, or in motion across on-premises and the cloud is essential to keep data safe and secure. This enables companies to identify their riskiest users and behaviors. With Forcepoint, you can automate the identification, classification, and protection of critical data. This webinar explores how companies should rethink data security. Protecting critical data and intellectual property requires a risk-adaptive, dynamic approach, including these three main components. Analytics-Driven Visibility – to gain oversight everywhere users work and collaborate Risk-Adaptive Controls – to eliminate the complexity of policy enforcement Intelligent & Dynamic Automation – to build a better understanding of c
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Forcepoint
Published By: IBM     Published Date: Jul 05, 2018
Scalable data platforms such as Apache Hadoop offer unparalleled cost benefits and analytical opportunities. IBM helps fully leverage the scale and promise of Hadoop, enabling better results for critical projects and key analytics initiatives. The end-to- end information capabilities of IBM® Information Server let you better understand data and cleanse, monitor, transform and deliver it. IBM also helps bridge the gap between business and IT with improved collaboration. By using Information Server “flexible integration” capabilities, the information that drives business and strategic initiatives—from big data and point-of- impact analytics to master data management and data warehousing—is trusted, consistent and governed in real time. Since its inception, Information Server has been a massively parallel processing (MPP) platform able to support everything from small to very large data volumes to meet your requirements, regardless of complexity. Information Server can uniquely support th
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IBM
Published By: IBM     Published Date: Jul 09, 2018
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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IBM
Published By: Tricentis     Published Date: Jan 08, 2018
Data. It seems to be everywhere today and yet we can never get enough of it. But as it turns out, a lack of data isn’t our problem -- our problem is the difficulty piecing together, understanding and finding the story in all the data that’s in front of us. In software testing in particular, the need for consolidated, meaningful test metrics has never been higher. As both the pace of development and the cost of delivering poor quality software increase, we need these metrics to help us test smarter, better and faster. Fortunately, business intelligence now exists to make this goal a reality. The analytics these tools provide can help drive efficient and effective testing by providing teams with insight on everything from testing quality and coverage to velocity and more. And this knowledge can position the QA team as trusted experts to advise the entire software development team on steps that can ensure a better quality end result.
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Tricentis
Published By: Hitachi Vantara     Published Date: Aug 02, 2018
In this inforgraphic, we are going to show you the possibilities with modernised, optimized data infrastructure. In doing so, we aim to bring you ideas about how you can bring your own data-driven business vision to life, focusing on the outcomes that matter most to you. In essence, we will be discussing five main industries and the possibilities for modernized data infrastructure. We will be displaying how Banking and Financial Services, Telecommunications, manufacturing, healthcare and retail can use data, analytics and automation to optimize their business, therefore bringing about a competitive edge which previous appeared unimaginable. Using data correctly, most importantly building proper data infrastructures, can be the driving force behind obtaining a competitive edge. Data is your story. And it’s our story, too.
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digital transformation, data infrastructure, data optimisation
    
Hitachi Vantara
Published By: Hitachi Vantara     Published Date: Aug 13, 2018
In this inforgraphic, we are going to show you the possibilities with modernised, optimized data infrastructure. In doing so, we aim to bring you ideas about how you can bring your own data-driven business vision to life, focusing on the outcomes that matter most to you. In essence, we will be discussing five main industries and the possibilities for modernized data infrastructure. We will be displaying how Banking and Financial Services, Telecommunications, manufacturing, healthcare and retail can use data, analytics and automation to optimize their business, therefore bringing about a competitive edge which previous appeared unimaginable. Using data correctly, most importantly building proper data infrastructures, can be the driving force behind obtaining a competitive edge. Data is your story. And it’s our story, too.
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Hitachi Vantara
Published By: Oracle     Published Date: Jan 09, 2019
Speed has become the necessary basis of competition. See how Oracle aims to help clients with this through their vision for autonomous database.
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Oracle
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
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