data insights

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By: IBM     Published Date: Sep 02, 2014
With tougher regulations and continuing market volatility, financial firms are moving to active risk management with a focus on counterparty risk. Firms are revamping their risk and trading practices from top to bottom. They are adopting new risk models and frameworks that support a holistic view of risk. Banks recognize that technology is critical for this transformation, and are adding state-of-the-art enterprise risk management solutions, high performance data and grid management software, and fast hardware. Join IBM Algorithmics and IBM Platform Computing to gain insights on this trend and on technologies for enabling active "real-time" risk management.
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     IBM
By: HERE Technologies     Published Date: May 24, 2019
How secure is your company’s network? The rising frequency of employee network access is fast becoming one of the most prevalent and unmanaged risks to the protection of critical enterprise data. When coupled with increasingly sophisticated cyber-attacks, the possibility of a security breach of enterprise networks becomes more likely. As one of the world’s leading location platforms in 2018, HERE shares insights and solutions to preventing identity fraud. Discover the latest facts and statistics. Learn more about the use-case of location verification when logging into your company’s network. Download the infographic from HERE Technologies.
Tags : technology, mapping, location data
     HERE Technologies
By: Cisco EMEA     Published Date: Mar 26, 2019
Most organizations have invested, and continue to invest, in people, processes, technology, and policies to meet customer privacy requirements and avoid significant fines and other penalties. In addition, data breaches continue to expose the personal information of millions of people, and organizations are concerned about the products they buy, services they use, people they employ, and with whom they partner and do business with generally. As a result, customers are asking more questions during the buying cycle about how their data is captured, used, transferred, shared, stored, and destroyed. In last year’s study (Cisco 2018 Privacy Maturity Benchmark Study), Cisco introduced data and insights regarding how these privacy concerns were negatively impacting the buying cycle and timelines. This year’s research updates those findings and explores the benefits associated with privacy investment. Cisco’s Data Privacy Benchmark Study utilizes data from Cisco’s Annual Cybersecurity Benchma
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     Cisco EMEA
By: IBM APAC     Published Date: May 14, 2019
Clients can realize the full potential of artificial intelligence (AI) and analytics with IBM’s deep industry expertise, technology solutions and capabilities and start to infuse intelligence into virtually every business decision and process. IBM’s AI & Analytics Services organization is helping enterprises get their data ready for AI and ultimately achieve stronger data-driven decisions; access deeper insights to provide improved customer care; and develop trust and confidence with AI-powered technologies focused on security, risk and compliance. Artificial intelligence (AI) is moving beyond the hype cycle, as more and more organizations seek to adopt AI-related technologies. These organizations are focusing on prioritizing functional areas and use cases, placing a stronger emphasis on topline growth, taking up a renewed interest in their data infrastructure and articulating greater unease about the skills of their knowledge workers. This report explores how they are approaching str
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     IBM APAC
By: IBM APAC     Published Date: May 14, 2019
Machine Learning For Dummies, IBM Limited Edition, gives you insights into what machine learning is all about and how it can impact the way you can weaponize data to gain unimaginable insights. Your data is only as good as what you do with it and how you manage it. In this book, you discover types of machine learning techniques, models, and algorithms that can help achieve results for your company. This information helps both business and technical leaders learn how to apply machine learning to anticipate and predict the future. You will find topics like: - What is machine learning? - Explaining the business imperative - The key machine learning algorithms - Skills for your data science team - How businesses are using machine learning - The future of machine learning
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     IBM APAC
By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
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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     Group M_IBM Q2'19
By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
As the information age matures, data has become the most powerful resource enterprises have at their disposal. Businesses have embraced digital transformation, often staking their reputations on insights extracted from collected data. While decision-makers hone in on hot topics like AI and the potential of data to drive businesses into the future, many underestimate the pitfalls of poor data governance. If business decision-makers can’t trust the data within their organization, how can stakeholders and customers know they are in good hands? Information that is not correctly distributed, or abandoned within an IT silo, can prove harmful to the integrity of business decisions.
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     Group M_IBM Q2'19
By: Pure Storage     Published Date: Apr 15, 2019
This year, businesses will increasingly turn to AI to power their business transformation. Machine learning and deep learning workloads are quickly becoming a mission-critical workload in the enterprise data center. As an IT leader, are you ready for the impending wave of AI applications that will demand new approaches to computing, storage and networking? Do you have the right strategy for scaling AI workload in your data center? We’ll introduce you to the IT visionaries who have made it happen. In this webinar we’ll explore how one IT leader accelerated his company’s success with an AI infrastructure strategy, sharing their best practices and insights. By watching this webinar, you'll learn: - Why it’s now critical for enterprise IT to have an AI infrastructure strategy that supports the business - Explore one IT leader’s experience developing and implementing a best-of-breed platform for scaling AI workload in the data center - Gain insights that can drive your AI infrastructur
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     Pure Storage
By: Verisign     Published Date: May 31, 2017
Verisign has a unique view into distributed denial of service (DDos) attack trends, including attack statistics, behavioral trends and future outlook. The below data contains observations and insights about attack frequency and size derived from mitigations enacted on behalf of customers of Verisign DDoS Protection Services from January through March 2017.
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     Verisign
By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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     Cisco
By: Zaloni     Published Date: Apr 23, 2019
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
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     Zaloni
By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
"Extracting value from data is central to the digital transformation required for businesses to succeed in the decades to come. Buried in data are insights that reveals what your customers need and how they want to receive it, how sales, manufacturing, distribution, and other aspects of business operations are functioning, what risks are arising to threaten the business, and more. That insight empowers your businesses to reach new customers, develop and deliver new products, to operate more efficiently and more effectively, and even to develop new business models. "
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
The bar for success is rising in higher education.  University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
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     Hewlett Packard Enterprise
By: HERE Technologies     Published Date: Mar 11, 2019
Increasingly sophisticated location technology makes it possible for data scientists to gain a deeper understanding of their target audiences – and how to reach them. Accurate and precise intelligence can give more timely and complete insights into audiences than ever before. As one of the world’s leading location platforms in 2018, HERE shares insights and solutions to buying location data for better audience segmentation.
Tags : location data, ad tech, location targeting
     HERE Technologies
By: Cisco EMEA     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
Tags : big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
     Cisco EMEA
By: Spectrum Enterprise     Published Date: Mar 01, 2019
FRONTEO provides end-to-end project management, litigation consulting and eDiscovery solutions for a global base of law firms and corporations. To meet clients’ critical information needs, the business requires connectivity and data center solutions that can process, access and interpret terabytes of sensitive data—reliably and at top speeds. Get actionable insights from experts at FRONTEO and learn how switching to a high-performance Ethernet solution from Spectrum Enterprise can deliver security and reliability across your network and IT infrastructure.
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     Spectrum Enterprise
By: Hitachi Vantara     Published Date: Mar 08, 2019
Business leaders recognize that their industries and markets are either being disrupted or have the potential to be disrupted by nimble digital players. In order to compete, senior IT leaders need to modernize their data centers. In this Forbes Insights Executive Briefing, learn how to embrace an agile data infrastructure, modern data protection, and intelligent operations to reap the benefits of a truly modernized data center.
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     Hitachi Vantara
By: Hitachi Vantara     Published Date: Mar 08, 2019
Technology is a fast-moving target, and organizations need agility and flexibility to compete. By modernizing your data center and maximizing the value of your corporate data, your company can gain those qualities. In this Forbes Insights checklist, learn how to derive value from your corporate data and embrace three elements of a modernized data center: an agile data infrastructure, a modern approach to data protection, and intelligent data center operations.
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     Hitachi Vantara
By: SAP     Published Date: May 18, 2014
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
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