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Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
The convergence between new technologies - like AI, blockchain, intelligent sensors, and edge computing - have the potential to disrupt, transform and streamline traditional supply chain operations. Join Supply Chain experts to learn: - Successes and failures of manufacturer’s to-date - Tips for selecting the best use case for your business - Industry best-practices for applying AI and blockchain
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Feb 25, 2019
The advantages blockchain can bring to the automotive ecosystem, both in facilitating collaboration among participants and enabling capabilities for new mobility business models, have gotten the attention of automotive executives. In addition to enabling a single source of data, blockchain can facilitate device-to-device transactions, smart contracts, and real-time processing and settlement. For the automotive industry, this translates into improvements and operational efficiencies in areas such as supply chain transparency, financial transactions between ecosystem participants, authenticating access to cars, and customer experience and loyalty.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Feb 28, 2019
Companies of all sizes have a critical need to match supply and demand as efficiently as possible, in order to quickly capture maximum demand at the lowest possible cost. This tutorial will walk you through a demand forecasting and planning solution that can help you deliver more accurate demand forecasts, optimized operations to satisfy demand, and a complete operational and financial plan that the business can use in practice. In this tutorial, you will explore the following key capabilities: Improve decision-making in a single workspace with IBM Planning Analytics Deliver timely, reliable plans and forecasts with the addition of SPSS Modeler Create optimal demand plans with the addition of IBM ILOG CPLEX Optimization Studio
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 01, 2019
Security leaders across all industries face mounting challenges. Cyberattacks are continually growing in volume, complexity, and sophistication, and incident response (IR) teams are pushed to the limit of their time, skill, and resources. Additionally, the average Security Operation Center (SOC) uses more than 75 different security tools – making full visibility nearly impossible and integrating those tools challenging as well.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 01, 2019
The velocity of technology infrastructure change continues to accelerate, putting serious stress on Security Operations (SecOps). This has forced security folks to face the fact that operations has never really been their forte. That’s a bit harsh, but denial never helps address problems. The evidence is fairly strong that most organizations are pretty bad at security operations. How many high-profile breaches could have been avoided if one of many alerts was acted upon? How many attacks were made possible by not having properly patched servers or infrastructure? How many successful compromises resulted from human error?
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 05, 2019
In this digital world, fast and reliable movement of digital data, including massive sizes over global distances, is becoming vital to business success across virtually every industry. The Transmission Control Protocol (TCP) that has traditionally been the engine of this data movement, however, has inherent bottlenecks in performance (Figure 1), especially for networks with high, round-trip time (RTT) and packet loss, and most pronounced on high-bandwidth networks. It is well understood that these inherent “soft” bottlenecks arcaused by TCP’s AdditiveIncrease-Multiplicative-Decrease (AIMD) congestion avoidance algorithm, which slowly probes the available bandwidth of the network, increasing the transmission rate until packet loss is detected and then exponentially reducing the transmission rate. However, it is less understood that other sources of packet loss, such as losses due to the physical network media, not associated with network congestion equally reduce the transmission rate.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 05, 2019
The Aspera FASP high speed transport platform is enabled to provide high-performance secure WAN transport of files, directories, and other large data sets to, from and between a number of leading third-party cloud storage platforms. The implementation is an enhanced transport stack and virtual file system layer in the Aspera server software that allows for direct-to-object-storage transfer over the WAN using the FASP protocol and the native I/O capabilities of the particular third-party file system. The stack is available in all generally available Aspera server software products and supports interoperable transfer with all generally available Aspera client software
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 05, 2019
For years, executives have been automating for efficiency, freeing workers from repetitive tasks, streamlining the back office and looking for cost savings. Now, they are exploring intelligent automation to establish thinking processes—processes that communicate realtime insights to employees, customers and partners across an expanding ecosystem. The ability to add intelligence to automation opens a new universe of possibilities that will have a profound impact on the way organizations operate and the way work gets done. More than anything else, intelligent automation will be a defining factor for the future workforce.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 05, 2019
Check out the IBM Marketplace where you can explore hundreds of IBM and partner products and services that make you and your business smarter
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 05, 2019
IBM commissioned Forrester Consulting to examine the potential ROI enterprises may realize by implementing the IBM Automation Platform for Digital Business. The purpose of this Total Economic Impact (TEI) study is to provide readers with a framework to evaluate the potential financial impact of the IBM Automation Platform for Digital Business on their organizations.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
This report explores a new breed of data warehouse that can operate in a world of legacy on-premise systems while exploiting the potential of cutting edge technologies and deployment styles
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
In this report, we'll analyze the many challenges that organizations face when it comes to building and managing a modern IT infrastructure
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
The days when avoiding the Cloud was a defensible position for a business are gone. By taking advantage of the Cloud, organizations not only gain its direct benefits, but are also better able to leverage other new technologies and become more efficient and innovative
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud
Tags : 
    
Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
In this paper, we focus on the DWA and how it has evolved over the years since its introduction. The XDW architecture is then described, in which the need to maintain the data warehouse is documented while adding new components and capabilities to extend the analytical capabilities. This section also discusses the appropriate usage of appliances within the XDW. The rest of the paper covers the benefits from implementing the DWA, the selection considerations for them and what the future holds for them.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
The life of an enterprise architect is becoming busy and difficult. Before the era of big data, the enterprise architect “only” had to worry about the data and systems within their own data center. However, over the past decade there were revolutionary changes to the way information is used by businesses and how data management platforms support the information available from modern data sources.
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: Mar 29, 2019
The vast increase in dark data—all of the unstructured data from the Internet, social media, voice and information from connected devices—is overwhelming many executives and leaving them completely unprepared for the challenges their businesses face.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Mar 29, 2019
Banking engagement is about to come full circle. Over the past few decades, banks have pushed customers to digital and self-service channels, with significant consequences. As customers take their transactions from the branches to the digital channels, banking has become less and less personal. Will this trend continue? To predict the future let’s first review how we got here.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
In Forrester's evaluation of the emerging market for conversational computing platforms, we identified the seven most significant providers — Amazon, Google, IBM, Microsoft, Nuance Communications, Oracle, and Rulai — in the category and evaluated them. This report details our findings about how each vendor scored against nine criteria and where they stand in relation to each other. Application developers should use this review to select the right partners for their conversational computing platform needs.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
Delivering personalized customer experience remains the top business challenge for communications service providers (CSPs). Ovum's recently published 2018 ICT Enterprise survey saw almost all CSP IT executives interviewed identify delivering personalized customer experience as one of their three most important business challenges for the next 18 months. This trend emphasizes the high priority CSPs place on how customer relationships are managed. However, several factors have an impact on CSPs' ability to identify and then deliver customers' core needs. These include understanding the data sets they should focus on; collecting, cleansing, and consolidating these data sets; and having the right expertise to mine the data sets.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
IDC strongly believes that the days of homogenous compute, in which a single architecture dominates all compute in the datacenter, are over. This truth has become increasingly evident as more and more businesses have started to launch artificial intelligence (AI) initiatives. Many of them are in an experimental stage with AI and a few have reached production readiness, but all of them are cycling unusually fast through infrastructure options to run their newly developed AI applications and services on.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
Power Systems are built for the most demanding, data-intensive, computing on earth. Our cloud-ready servers help you unleash insight from your data pipeline—from managing mission-critical data, to managing your operational data stores and data lakes, to delivering the best server for cognitive computing.
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Group M_IBM Q2'19
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