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big data analysis

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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: 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: 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: 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 design and management, data center
    
Collaborative Consulting
Published By: SAS     Published Date: Nov 04, 2015
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.
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data visualization, sas, big data, visual analytics, data exploration, analysis, networking, knowledge management, data management
    
SAS
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 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.
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Oracle PaaS/IaaS/Hardware
Published By: TIBCO Software APAC     Published Date: Aug 13, 2018
The popularity of integration platform as a service (iPaaS) started with business users looking to gain control and share data among their proliferating SaaS apps?without needing IT intervention. iPaaS was then adopted by IT to support business users to ensure security measures were being maintained and to provide more of a self-service environment. Now, iPaaS has evolved from a niche solution to taking a much bigger role: Read this whitepaper to learn about: Drivers for cloud integration Five emerging uses cases for iPaaS that enable better responsiveness, APIs, event-driven capabilities, human workflows, and data analysis Questions to ask when evaluating your current solution
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TIBCO Software APAC
Published By: SAP     Published Date: Jul 20, 2015
However, here at SAP we have identified four broad technology trends that are currently having a major impact on how retailers conduct business and engage with consumers. They are Big Data, social media, seamless retailing and disruptive technologies. Read this report for an analysis and overview of each trend area, why they are important and what the future likely holds.
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it trends, retail, big data, social media, seamless retailing, disruptive technology, trends
    
SAP
Published By: Waterline Data & Research Partners     Published Date: May 18, 2015
Waterline Data automates the cataloging of data assets and provides an Amazon.com-like guided shopping approach to data discovery that is intended to take the guesswork out of targeting the right data.
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waterline, big data, automation, cataloging, processing, analysis, assets, data science, data management, data integration, data warehousing, virtualization, cloud computing, infrastructure, design and facilities
    
Waterline Data & Research Partners
Published By: Waterline Data & Research Partners     Published Date: May 18, 2015
In this report, Forrester Research recommends that application development and delivery (AD&D) professionals working on BI and big data initiatives get the best out of both by designing and integrating them in a flexible data platform.
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waterline, big data, automation, cataloging, processing, analysis, assets, data science, data management, distributed computing, analytical applications, data warehousing, cloud computing, data center design and management, virtualization, infrastructure, design and facilities
    
Waterline Data & Research Partners
Published By: IBM     Published Date: Apr 14, 2017
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
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data integration, big data, data sources, business needs, technological advancements, scaling data
    
IBM
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. The biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation. The increasing volume, variety, and velocity of data is putting pressure on organizations to rethink traditional methods of preparing data for reporting, analysis, and sharing. Download this white paper to find out how you can improve your data preparation for business analytics.
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Waterline Data & Research Partners
Published By: IBM     Published Date: Oct 27, 2016
IBM Analytics for Apache Spark for Bluemix is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to other technologies on the market today. Optimized for extremely fast and large scale data processing-you can easily perform big data analysis from one application.
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ibm, apache spark, bluemix, analytics, enterprise applications
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
Analytics relies on BI, Big Data, and data discovery to provide reporting, trend what-if analysis. Analytics is transforming data into insight.
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ibm, analytics, business intelligence, data, data management
    
IBM
Published By: CEB     Published Date: Nov 21, 2013
How do you know if your organization has the talent it needs to execute on its strategy? Is your organization’s talent ready to perform in the new work environment? Are your talent development programs focused on the right people?
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ceb, big data, big data intent, global workforce, organisational talent, business objectives, productivity, innovation, talent management, workforce skills, data-based analysis, future leaders, organisational risk, global skills, landscape of diversity, global availability, best practices, business intelligence, business process management, employee performance
    
CEB
Published By: Topsy     Published Date: Jul 16, 2013
Marketing today is real-time, always-on, pervasive, and constant—but following these 5 simple rules guarantees that you’ll stand out from the crowd.
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twitter, advertising, real-time, realtime marketing, real-time marketing, social marketing, social strategy, social listening, social data, social analytics, social media analytics, social intelligence, data mining, big data, social media tools, social analysis tools, social media analysis tools, social media monitoring, social media monitoring tools, social media marketing
    
Topsy
Published By: Oracle     Published Date: Oct 20, 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 compani
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Oracle
Published By: Pentaho     Published Date: Apr 28, 2016
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.
Tags : 
pentaho, best practices, hadoop, next generation analytics, platforms, infrastructure, data, analytics in organizations, it management, wireless, enterprise applications, data management, data center
    
Pentaho
Published By: Amazon Web Services     Published Date: Aug 20, 2018
A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
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Amazon Web Services
Published By: Gemini Data     Published Date: Jan 16, 2018
The increasing reliance on big data platforms for all functions of the organization has been transformative. As these environments mature and data volumes increase, organizations face infrastructure and management scalability challenges. Gemini Enterprise Manager simplifies deployment and management with a turnkey, NoOps appliance, providing simplicity, security, and speed to accelerate the time to value for any analysis use case. Manager allows you to control your Splunk deployment as a single, unified solution deployed on premises, in the cloud or both.
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Gemini Data
Published By: EMC Corporation     Published Date: Aug 05, 2014
It’s an exciting yet daunting time to be a security professional. Security threats are becoming more aggressive and voracious. Governments and industry bodies are getting more prescriptive around compliance. Combined with exponentially more complex IT environments, security management is increasingly challenging. Moreover, new “Big Data” technologies purport bringing advanced analytic techniques like predictive analysis and advanced statistical techniques close to the security professional.
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big data, data management, security threats, advanced analytics, security management, predictive analytics, compliance, security, it management
    
EMC Corporation
Published By: HP     Published Date: Jan 20, 2015
There are many new ways Big Data analytics can significantly boost marketing and promotional efforts through real-time and historical analysis of online data, such as clickstream or purchase transactions. Unstructured data based on social media—even photos and video—offers enormous potential when analyzed with the right tools.
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big data, hp haven, scalable, secure data platform, ecosystem, security
    
HP
Published By: Datastax     Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
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evolution, big data, technology, datastax, nosql
    
Datastax
Published By: EMC Corporation     Published Date: Mar 20, 2014
The status quo approach of collecting more logs from more sources won't help in detecting and responding to advanced threats. Logs are inherently limited in the level security visibility that they provide. Consider a new way of looking at SIEM.
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emc, siem, security transformation, malware detection, malware threats, big data security platform, incident detection, advanced security analysis, security
    
EMC Corporation
Published By: EMC Corporation     Published Date: Mar 20, 2014
To develop the visibility, agility and speed to deal with advanced threats, security information and event management (SIEM) systems need to evolve into a central nervous system for large-scale security analytics.
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emc, siem, security transformation, malware detection, malware threats, big data security platform, incident detection, advanced security analysis, security
    
EMC Corporation
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