data analysis

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Published By: ETQ     Published Date: Jul 10, 2019
According to Gartner, "supply chain leaders responsible for quality management are shifting to software solutions that standardize processes, optimize data and ensure compliance. This research provides guidance for structuring a process for QMS software selection." Download this Gartner Analyst Guide to learn: Key challenges in the QMS software selection processes What to expect from different QMS solutions across the market Analysis of the current state of quality management to help define software requirements Self assessment questions and commonly sought QMS system functionalities to use in your decision making process
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ETQ
Published By: TIBCO Software     Published Date: Jul 22, 2019
Connected Intelligence in Insurance Insurance as we know it is transforming dramatically, thanks to capabilities brought about by new technologies such as machine learning and artificial intelligence (AI). Download this IDC Analyst Infobrief to learn about how the new breed of insurers are becoming more personalized, more predictive, and more real-time than ever. What you will learn: The insurance industry's global digital trends, supported by data and analysis What capabilities will make the insurers of the future become disruptors in their industry Notable leaders based on IDC Financial Insights research and their respective use cases Essential guidance from IDC
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TIBCO Software
Published By: Amazon Web Services EMEA     Published Date: Sep 09, 2019
Local and regional governments around the world are using the cloud to transform services, improve their operations, and reach new horizons for citizen services. The Amazon Web Services (AWS) cloud enables data collection, analysis, and decision making for smarter cities. This whitepaper provides strategic considerations for local and regional governments to consider as they identify which IT systems and applications to move to the cloud. Real examples that show how cities can stop wasting money, move faster, and innovate.
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Amazon Web Services EMEA
Published By: Group M_IBM Q3'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Group M_IBM Q3'19     Published Date: Sep 04, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Ounce Labs, an IBM Company     Published Date: Dec 15, 2009
Today, when you make decisions about information technology (IT) security priorities, you must often strike a careful balance between business risk, impact, and likelihood of incidents, and the costs of prevention or cleanup. Historically, the most well-understood variable in this equation was the methods that hackers used to disrupt or invade the system.
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ounce labs, it securitym it risk, software applications, pci dss, hipaa, glba, data security, source code vulnerabilities, source code analysis, it security, cryptography
    
Ounce Labs, an IBM Company
Published By: Ounce Labs, an IBM Company     Published Date: Jul 08, 2009
The Business Case for Data Protection, conducted by Ponemon Institute and sponsored by Ounce Labs, is the first study to determine what senior executives think about the value proposition of corporate data protection efforts within their organizations. In times of shrinking budgets, it is important for those individuals charged with managing a data protection program to understand how key decision makers in organizations perceive the importance of safeguarding sensitive and confidential information.
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ounce labs, it securitym it risk, software applications, ciso, pci dss, hipaa, glba, data security, source code vulnerabilities, source code analysis, it security, cryptography
    
Ounce Labs, an IBM Company
Published By: SAP     Published Date: Feb 03, 2017
The SAP HANA platform provides a powerful unified foundation for storing, processing, and analyzing structured and unstructured data. It funs on a single, in-memory database, eliminating data redundancy and speeding up the time for information research and analysis.
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SAP
Published By: HERE Technologies     Published Date: Jan 22, 2019
To improve safety and mobility across its 5,600km road network, the City of Toronto forged a partnered with HERE Technologies for the provision of traffic, incident, and historical traffic data. Access to this data allows the city authority to see exactly what’s happening on its roads and more easily and affectively run studies on improvement projects. This case study details how HERE Technologies enabled the City of Toronto’s transportation team to: Work smarter with comprehensive network coverage and accurate data to aid analysis Examine the impact of city projects without significant forward planning or expenditure Ensure travel volume models used to drive decision making are calibrated to represent real-world truths
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public sector, urbanization, traffic management
    
HERE Technologies
Published By: Cisco EMEA     Published Date: Mar 05, 2018
The operation of your organization depends, at least in part, on its data. You can avoid fines and remediation costs, protect your organization’s reputation and employee morale, and maintain business continuity by building a capability to detect and respond to incidents effectively. The simplicity of the incident response process can be misleading. We recommend tabletop exercises as an important step in pressure-testing your program.
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human resources, cisco, employees, data, analysis
    
Cisco EMEA
Published By: Oracle     Published Date: Nov 28, 2017
Today’s leading-edge organizations differentiate themselves through analytics to further their competitive advantage by extracting value from all their data sources. Other companies are looking to become data-driven through the modernization of their data management deployments. These strategies do include challenges, such as the management of large growing volumes of data. Today’s digital world is already creating data at an explosive rate, and the next wave is on the horizon, driven by the emergence of IoT data sources. The physical data warehouses of the past were great for collecting data from across the enterprise for analysis, but the storage and compute resources needed to support them are not able to keep pace with the explosive growth. In addition, the manual cumbersome task of patch, update, upgrade poses risks to data due to human errors. To reduce risks, costs, complexity, and time to value, many organizations are taking their data warehouses to the cloud. Whether hosted lo
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Oracle
Published By: Cisco EMEA     Published Date: Mar 14, 2018
What if defenders could see the future? If they knew an attack was coming, they could stop it, or at least mitigate its impact and help ensure what they need to protect most is safe. The fact is, defenders can see what’s on the horizon. Many clues are out there—and obvious. For years, Cisco has been warning defenders about escalating cybercriminal activity around the globe. In this, our latest annual cybersecurity report, we present data and analysis from Cisco threat researchers and several of our technology partners about attacker behavior observed over the past 12 to 18 months.
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Cisco EMEA
Published By: HP Enterprise Business     Published Date: Mar 02, 2017
Powered by data from 451 Research, the Right Mix web application benchmarks your current private vs public cloud mix, business drivers, and workload deployment venues against industry peers to create a comparative analysis. See how your mix stacks up, then download the 451 Research report for robust insights into the state of the hybrid IT market.
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HP Enterprise Business
Published By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
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pentaho, analytics, platforms, hadoop, big data, predictive analytics, networking, it management, knowledge management, data management
    
Pentaho
Published By: Cisco     Published Date: Jun 21, 2016
The demands on IT today are staggering. Most organizations depend on their data to drive everything from product development and sales to communications, operations, and innovation. As a result, IT departments are charged with finding a way to bring new applications online quickly, accommodate massive data growth and complex data analysis, and make data available 24 hours a day, around the world, on any device. The traditional way to deliver data services is with separate infrastructure silos for various applications, processes, and locations, resulting in continually escalating costs for infrastructure and management. These infrastructure silos make it difficult to respond quickly to business opportunities and threats, cause productivity-hindering delays when you need to scale, and drive up operational costs.
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Cisco
Published By: Adobe     Published Date: Nov 09, 2017
Patients are going digital — and taking the healthcare system with them. Learn how in the 2017 Digital Trends in Healthcare and Pharma report. Download it now to learn: Why two-thirds of healthcare companies are investing in data analysis. How they’re building content marketing programs to boost patient knowledge. What they plan to do with virtual and augmented reality this year and beyond.
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Adobe
Published By: Oracle CX     Published Date: Oct 19, 2017
In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical. These challenges have dramatically changed the way that IT systems are architected, provisioned, and run compared to the past few decades. Most companies
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle CX
Published By: IBM APAC     Published Date: Nov 22, 2017
Glossary:Terms You Should Know Take your data analysis and deep learning expertise to the next level with these industry terms.
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api, application, programming, interface, artificial intelligence, base, encoding, chrome, code page
    
IBM APAC
Published By: Delphix     Published Date: May 03, 2016
Data security is a top concern these days. In a world of privacy regulation, intellectual property theft, and cybercrime, ensuring data security and protecting sensitive enterprise data is crucial. Only a data masking solution can secure vital data and enable outsourcing, third-party analysis, and cloud deployments. But more often than not, masking projects fail. Some of the best data masking tools bottleneck processes and once masked, data is hard to move and manage across the application development lifecycle.
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Delphix
Published By: Dell EMC     Published Date: Nov 09, 2015
Download this whitepaper and learn how the Dell Genomic Data Analysis Platform can accelerate discovery and insights through optimized infrastructure and support.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
Download this whitepaper for: • An overview of how manufacturing can benefit from the big data technology stack • A high-level view of common big data pain points for manufacturers • A detailed analysis of big data technology for manufacturers • A view as to how manufacturers are going about big data adoption • A proven case study with: Omneo
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Dell EMC
Published By: Dell     Published Date: Jan 26, 2015
Forrester presents the relevant endpoint security data from their most recent surveys, with special attention given to those trends affecting SMBs (firms with 20 to 999 employees) and enterprises (firms with 1,000+ employees), along with analysis that explains the data in the context of the overall security landscape. As organizations prepare for the 2015 budget cycle, security and risk (S&R) professionals should use this annual report to help benchmark their organization’s spending patterns against those of their peers — while keeping an eye on current trends affecting endpoint security — in order to strategize their endpoint security adoption decisions. Please download this Forrester Research report, offered compliments of Dell, for more information.
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dell, windows, endpoint security adoption, forrester, smbs, budget cycle, security
    
Dell
Published By: Collaborative Consulting     Published Date: Dec 20, 2013
The explosion of Big Data represents an opportunity to leverage trending attitudes in the marketplace to better segment and target customers, and enhance products and promotions. Success requires establishing a common business rationale for harnessing social media and determining a maturity model for sentiment analysis to assess existing social media capabilities.
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collaborative consulting, big data, social media, customer sentiment, influence sentiment, govern sentiment, maturity model, generate revenue, media promotions, measurable influence, maturity level, data management, data center
    
Collaborative Consulting
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