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Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
The current trend in manufacturing is towards tailor-made products in smaller lots with shorter delivery times. This change may lead to frequent production modifications resulting in increased machine downtime, higher production cost, product waste—and no need to rework faulty products. To satisfy the customer demand behind this trend, manufacturers must move quickly to new production models. Quality assurance is the key area that IT must support. At the same time, the traceability of products becomes central to compliance as well as quality. Traceability can be achieved by interconnecting data sources across the factory, analyzing historical and streaming data for insights, and taking immediate action to control the entire end-to-end process. Doing so can lead to noticeable cost reductions, and gains in efficiency, process reliability, and speed of new product delivery. Additionally, analytics helps manufacturers find the best setups for machinery.
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TIBCO Software GmbH
Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202
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TIBCO Software GmbH
Published By: Engagio     Published Date: Jan 14, 2019
B2B demand generation has almost completely re-invented itself over the last decade. The collision of inbound, content marketing, lead nurturing, marketing automation, analytics, email, search, social media and native advertising has transformed the discipline from a dark art to an increasingly data-driven science. But there’s a problem When it comes to helping to land and expand these major deals, today’s marketing teams are seriously handicapped. The Clear & Complete Guide to Account Based Marketing (ABM) is your guide to solving this problem. It will take you, step-by-step, through this fast-emerging discipline, showing you how to align your sales and marketing team around a strategy that’s optimized for the biggest, most important deals.
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Engagio
Published By: Attunity     Published Date: Jan 14, 2019
This whitepaper explores how to automate your data lake pipeline to address common challenges including how to prevent data lakes from devolving into useless data swamps and how to deliver analytics-ready data via automation. Read Increase Data Lake ROI with Streaming Data Pipelines to learn about: • Common data lake origins and challenges including integrating diverse data from multiple data source platforms, including lakes on premises and in the cloud. • Delivering real-time integration, with change data capture (CDC) technology that integrates live transactions with the data lake. • Rethinking the data lake with multi-stage methodology, continuous data ingestion and merging processes that assemble a historical data store. • Leveraging a scalable and autonomous streaming data pipeline to deliver analytics-ready data sets for better business insights. Read this Attunity whitepaper now to get ahead on your data lake strategy in 2019.
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data lake, data pipeline, change data capture, data swamp, hybrid data integration, data ingestion, streaming data, real-time data, big data, hadoop, agile analytics, cloud data lake, cloud data warehouse, data lake ingestion, data ingestion
    
Attunity
Published By: Hitachi     Published Date: Jan 11, 2019
Making sense of your data is one of the greatest challenges facing business today. Imagine a world where innovation and time-to-value are accelerated by AI and automation. Hitachi Vantara works at every point along the data value chain from analytics and insight, through intelligent governance to efficient, agile storage. Download this e-book to find out how to turn the business-enabling capital of the digital era into sustainable value.
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Hitachi
Published By: Workday     Published Date: Jan 09, 2019
Artificial intelligence (AI) and machine learning are redefining business analytics. But for HR, use cases can be much more complex. Learn five key steps to build a strong foundation for answering HCM questions today and position yourself to use AI in HR going forward.
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Workday
Published By: Workday     Published Date: Jan 09, 2019
In this Argyle Executive Forum webinar, leading HR executives across industries provide expert insight and recommendations for building an analytics strategy and putting a data foundation in place.
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Workday
Published By: Oracle     Published Date: Jan 09, 2019
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Oracle
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: Epicor     Published Date: Jan 09, 2019
Behind the scenes of the world’s leading industrial and manufacturing companies, a profound digital transformation is now underway .1 As with any profound transformation, the opportunities for competitive advantage and growth are enormous, but so are the challenges . How do you determine what your next digital transformation steps should be? How do you position your manufacturing business to take the next step—and the one after that? This eBook will help you answer these questions . In it we will: XX Introduce the role of visibility in digital transformation XX Consider three key trends that are shaping the future of manufacturing by delivering the visibility that enables transformation: – Growth of the Internet of Things (IoT) – The advance of analytics – The migration of applications to the cloud XX Identify the traits you need in your core systems to take advantage of these trends—giving you the visibility to identify and take the steps that will help transform your business into
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Epicor
Published By: Esker     Published Date: Jan 08, 2019
Ignoring the potential of AR analytics is a losing game. In order to boost your collection rate and maximize resources, departments should be analyzing a plethora of statistics — not just DSO. This playbook discusses the six metrics your AR department should be paying attention to and how they can separate themselves from competition and provide customers with an improved experience by: • Measuring Key Performance Indicators (KPIs) • Making process improvements based on analytics • Centralizing collection activities
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Esker
Published By: Lenovo and Intel®     Published Date: Jan 08, 2019
If you are trying to process, understand, and benefit from "big data," you need SAP® HANA®. In-memory database Process data at extreme speeds Real-time analytics and insights If you want to make sure you have access to your data for insights, whenever and wherever you need them, then SAP HANA on Lenovo's future-defined infrastructure—powered by the Intel® Xeon® Platinum processor—delivers what you need. Get the details on everything you need to know about the value of SAP HANA, why SAP chose Lenovo for their own HANA installation, and how Lenovo can help your organization today.
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sap hana, lenovo, intel, big data, database, analytics, insights
    
Lenovo and Intel®
Published By: Group M_IBM Q119     Published Date: Jan 08, 2019
The discipline of data quality assurance ensures that data is "fit for purpose" in the context of existing business operations, analytics and emerging digital business scenarios. It covers much more than just technology. It includes program management, roles, organizational structures, use cases and processes (such as those for monitoring, reporting and remediating data quality issues). It is also linked to broader initiatives in the field of enterprise information management (EIM), including information governance and master data management (MDM)
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Group M_IBM Q119
Published By: Forcepoint     Published Date: Jan 07, 2019
Security spending is expected to reach $120 billion by 2021, yet the amount of data loss events seems to be increasing. Legacy DLP solutions, which rely on traditional threat blocking policies, have been unable to evolve to address these threats. Watch this webcast to understand how taking a Risk-Adaptive approach enables security to fluctuate based on the threat environment.
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data protection, data loss prevention, data leak prevention, data security, risk-adaptive, critical data, intellectual property protection, cybersecurity, cyber security, analytics, behavior analytics, dlp, data centric security
    
Forcepoint
Published By: Forcepoint     Published Date: Jan 07, 2019
We are only beginning to see the impact of predictive analytics upon cybersecurity – especially for insider threat detection and prevention. Watch this webcast where we examine the technologies which make predictive analytics valuable, along with ethically minded guidance to strike the balance between vigilance and privacy.
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analytics, behavioral analytics, ueba, insider threat, cybersecurity, predictive analytics, behavior analytics, security analytics, risk, risk adaptive
    
Forcepoint
Published By: Forcepoint     Published Date: Jan 07, 2019
We are only beginning to see the impact of predictive analytics upon cybersecurity – especially for insider threat detection and prevention. Watch this webcast where we examine the technologies which make predictive analytics valuable, along with ethically minded guidance to strike the balance between vigilance and privacy.
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analytics, behavioral analytics, ueba, insider threat, cybersecurity, predictive analytics, behavior analytics, security analytics, risk, risk adaptive
    
Forcepoint
Published By: Forcepoint     Published Date: Jan 07, 2019
Things are not as they used to be in the enterprise. Today’s employees are mobile, they’re storing and accessing data in cloud apps, and are in disparate networks. Yet, the threat-centric security approach, with its static policies forces decisions about cyber activity with no insight into the broader context. The result is a disproportionate number of flagged activities, overwhelming security teams who have no way to understand the ones most worthy of investigation. Read Rethinking Data Security with a Risk-Adaptive Approach to learn how a human-centric, risk-adaptive approach can help your organization be more proactive
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data protection, data loss prevention, data leak prevention, data security, risk-adaptive, critical data, intellectual property protection, cybersecurity, cyber security, analytics, behavior analytics, dlp, data centric security
    
Forcepoint
Published By: Forcepoint     Published Date: Jan 07, 2019
Security spending is expected to reach $120 billion by 2021, yet the amount of data loss events seems to be increasing. Legacy DLP solutions, which rely on traditional threat blocking policies, have been unable to evolve to address these threats. Watch this webcast to understand how taking a Risk-Adaptive approach enables security to fluctuate based on the threat environment.
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data protection, data loss prevention, data leak prevention, data security, risk-adaptive, critical data, intellectual property protection, cybersecurity, cyber security, analytics, behavior analytics, dlp, data centric security
    
Forcepoint
Published By: Oracle     Published Date: Jan 06, 2019
After talking to 27 leading CFOs, the Economist Intelligence Unit finds that the finance team’s data analytics skills put the CFO in the driving seat of digital change. The result is that the CFO has a new responsibility to: • Help other business units meet their digital ambitions • Make relevant data visible across the business • Develop goals and metrics for digital success Watch the webinar
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Oracle
Published By: SAS     Published Date: Jan 04, 2019
How can you open your analytics program to all types of programming languages and all levels of users? And how can you ensure consistency across your models and your resulting actions no matter where they initiate in the company? With today’s analytics technologies, the conversation about open analytics and commerical analytics is no longer an either/or discussion. You can now combine the benefits of SAS and open source analytics technology systems within your organization. As we think about the entire analytics life cycle, it’s important to consider data preparation, deployment, performance, scalability and governance, in addition to algorithms. Within that cycle, there’s a role for open source and commercial analytics. For example, machine learning algorithms can be developed in SAS or Python, then deployed in real-time data streams within SAS Event Stream Processing, while also integrating with open systems through Java and C APIs, RESTful web services, Apache Kafka, HDFS and more.
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SAS
Published By: SAS     Published Date: Jan 04, 2019
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment. Newer examples of operational analytics include support for logistics, customer call centers, fraud detection, and recommendation engines to name just a few. Embedding analytics is certainly not new but has been gaining more attention recently as data volumes and the freq
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SAS
Published By: Veritas     Published Date: Jan 04, 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: Sage     Published Date: Jan 04, 2019
Do you know your people as well as you know your customers? Your people’s expectations and the way they work is changing. Employees are more diverse, mobile and technologically-savvy than ever before. HR processes are changing from focusing on transactions to knowing and engaging people. Just as sales and marketing teams use data to develop actionable and informed insights about their customers, you need to do the same in HR to know your people. Everything, from attracting and keeping the best talent, to creating better workplace experiences and increasing employee engagement and productivity, depends on smarter decisions. These in turn rely on more actionable insights. These are only possible through accurate HR data and analytics. They are vital to address the people challenges you face, so you can make smarter decisions. Discover in this guide how to improve visibility of your workforce with data-driven and actionable insights. Ultimately, it will help you know your people
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Sage
Published By: Group M_IBM Q119     Published Date: Jan 04, 2019
Digital transformation is poised to change the supply chain more profoundly than any other functional area and more dramatically than at any point in its history in terms of driving efficiency and resiliency to disruption. In the context of the challenges facing supply chains, both now and in the future, it becomes clear that the old ways of working will not suffice and that even best-in-class performance today is unlikely to be good enough in the future. It is the view of IDC that the supply chain must become a "thinking" supply chain, one that is intimately connected to all data sources, enabled with comprehensive and fast analytics, openly collaborative through cloud-based commerce networks, conscious of cyberthreats, and cognitively interwoven. According to IDC supply chain research, technology is emerging as a prime driver of change, particularly artificial intelligence, blockchain, and the Internet of Things (IoT).
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Group M_IBM Q119
Published By: AWS     Published Date: Jan 03, 2019
Managing your data can be a challenge, but establishing an analytics solution that every user can navigate, regardless of skillset, is where organizations often need help. TIBCO® Spotfire® features AI-driven data visualizations and dashboards, which helps enables each organizational role to discover and deliver valuable insights with ease. Riteway Sales and Marketing, which helps many Southeastern supermarkets execute strategies, leveraged the power of TIBCO Spotfire to better understand individual product performance throughout their stores, achieving exponentially faster time to insight than their previous solution allowed. Watch this on-demand webinar to learn how TIBCO Spotfire, when leveraged on Amazon Web Services cloud, can help you generate deep insights in minutes. You’ll learn: • How to generate relevant, actionable insights from any data, anywhere • Some of the best practices for leveraging AI-driven visual and predictive analytics solutions in the cloud • How to
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AWS
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