advanced data analytics

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By: Impetus     Published Date: Feb 04, 2016
This white paper explores strategies to leverage the steady flow of new, advanced real-time streaming data analytics (RTSA) application development technologies. It defines a thoughtful approach to capitalize on the window of opportunity to benefit from the power of real-time decision making now, and still be able to move to new and emerging technologies as they become enterprise ready.
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     Impetus
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.
Tags : pentaho, analytics, platforms, hadoop, big data, predictive analytics, data science
     Pentaho
By: SAP     Published Date: Dec 04, 2015
Download this whitepaper to see how advanced technologies such as big data, cloud computing, mobile devices, and enterprise access to in-memory platforms, predictive analytics, and planning software can help CFOs make better and more sophisticated use of data, influence decisions, and take practical, timely action.
Tags : finance function, finance, cfo, big data, cloud computing, mobile, in-memory platforms, predictive analytics, planning software
     SAP
By: Secureworks ABM UK 2017     Published Date: Oct 23, 2017
SecureWorks provides an early warning system for evolving cyber threats, enabling organisations to prevent, detect, rapidly respond to and predict cyber attacks. Combining unparalleled visibility into the global threat landscape and powered by the Counter Threat Platform — our advanced data analytics and insights engine —SecureWorks minimises risk and delivers actionable, intelligence driven security solutions for clients around the world.
Tags : cyber security, cyber security framework, data security, firewall, general data protection regulation, incident and problem management, information security, intrusion detection, intrusion prevention, log management, malware, vulnerabilities, managed security services, network security, pci compliance, penetration testing, ransomware security consulting, security management, security monitoring, vulnerability assessments
     Secureworks ABM UK 2017
By: Intel     Published Date: Dec 13, 2018
In today’s world, advanced vision technologies is shaping the next era of Internet of Things. However, gathering streaming video data is insufficient. It needs to be timely and accessible in near-real time, analyzed, indexed, classified and searchable to inform strategy—while remaining cost-effective. Smart cities and manufacturing are prime examples where complexities and opportunities have been enabled by vision, IoT and AI solutions through automatic meter reading (AMR), image classification and segmentation, automated optical inspection (AOI), defect classification, traffic management solution—just to name a few. Together, ADLINK, Touch Cloud, and Intel provide a turnkey AI engine to assist in data analytics, detection, classification, and prediction for a wide range of use cases across a broad spectrum of sectors. Learn more about how the Touch Cloud AI brings cost savings, operational efficiency and a more reliable, actionable intelligence at the edge with transformative insi
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     Intel
By: IBM     Published Date: Feb 02, 2016
Advanced analytics can provide extremelyvaluable insight into today’s media viewers. This must-read report details the top 10 best practices for successfully implementing data analytics for driving profit, attracting new viewers, and increasing viewer loyalty.
Tags : ibm, big data, analytics, media, entertainment, data analytics, data science
     IBM
By: IBM     Published Date: Jul 26, 2017
The headlines are ablaze with the latest stories of cyberattacks and data breaches. New malware and viruses are revealed nearly every day. The modern cyberthreat evolves on a daily basis, always seeming to stay one step ahead of our most capable defenses. Every time there is a cyberattack, government agencies gather massive amounts of data. To keep pace with the continuously evolving landscape of cyberthreats, agencies are increasingly turning toward applying advanced data analytics to look at attack data and try to gain a deeper understanding of the nature of the attacks. Applying modern data analytics can help derive some defensive value from the data gathered in the aftermath of an attack, and ideally avert or mitigate the damage from any future attacks.
Tags : cyber attacks, data breach, advanced data analytics, malware
     IBM
By: SAP     Published Date: Jul 18, 2016
Companies are finding more success with advanced analytics initiatives, allowing for continued innovation and experimentation. Read the report learn key findings from the survey carried out by The Economist Intelligence Unit, with Sponsorship by SAP.
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     SAP
By: TIBCO Software     Published Date: Jul 22, 2019
Today, you can improve product quality and gain better control of the entire manufacturing chain with data virtualization, machine learning, and advanced data analytics. With all relevant data aggregated, analyzed, and acted on, sensors, devices, people, and processes become part of a connected Smart Factory ecosystem providing: •? Increased uptime, reduced downtime •? Minimized surplus and defects •? Better yields •? Reduced cost due to better quality •? Fewer deviations and less non-conformance
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     TIBCO Software
By: MicroStrategy     Published Date: Jan 23, 2019
A&BI platforms are evolving beyond data visualization and dashboards to encompass augmented and advanced analytics. Data and analytics leaders should enable a broader set of users with new expanded capabilities to increase the business impact of their investments.
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     MicroStrategy
By: MicroStrategy     Published Date: Jun 06, 2019
A&BI platforms are transitioning from delivering simple, manual self-service to supporting more advanced, automated analytic use cases via growing, augmented, ML-driven capabilities. Data and analytics leaders should enable broader use cases to increase their investments’ business impact.
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     MicroStrategy
By: MicroStrategy     Published Date: Jun 06, 2019
A&BI platforms are transitioning from delivering simple, manual self-service to supporting more advanced, automated analytic use cases via growing, augmented, ML-driven capabilities. Data and analytics leaders should enable broader use cases to increase their investments’ business impact.
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     MicroStrategy
By: StreamSets     Published Date: Dec 05, 2018
Enterprise analytics is quickly evolving into a democratized capability where anyone can access and act on all available information, often in real-time employing advanced techniques. But the complex, dynamic and urgent nature of modern data analytics demands a new approach to data integration. This paper proposes that DataOps, the application of DevOps practices to data analytics, is the best way to overcome these challenges to create an iterative build-operate process for data movement. Read this white paper to: Understand how modern data analytics create data integration challenges due to architectural complexity, operational blindness and data drift. Learn how DevOps pillars of automation and monitoring can create higher developer productivity, operational efficiency and business confidence in data. See specific examples of DataOps functionality being applied to data integration across modern architectures.
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     StreamSets
By: StreamSets     Published Date: Feb 13, 2019
Enterprise analytics has quickly evolved from a centralized business intelligence function for historical reporting and dashboards to a democratized capability where anyone can access, analyze and act on all available information, often in real-time while employing advanced techniques. But the complex, dynamic and urgent nature of modern data analytics demands a new approach to data integration.
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     StreamSets
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
     Pentaho
By: Birst     Published Date: Jul 16, 2013
Discover seven indications that you need advanced analytics for your CRM application and why they matter. Learn about common CRM data analysis pain points and how advanced CRM analytics can solve them.
Tags : business intelligence, agile bi, self service bi, bi in the cloud, unified bi, mobile bi, embedded analytics, business analytics, sales analytics, hr analytics, marketing analytics, financial analytics, supply chain analytics, automated data management, dashboards, infrastructure
     Birst
By: EMC Corporation     Published Date: Aug 05, 2014
Large organizations can no longer rely on preventive security systems, point security tools, manual processes, and hardened configurations to protect them from targeted attacks and advanced malware. Henceforth, security management must be based upon continuous monitoring and data analysis for up-to-the-minute situational awareness and rapid data-driven security decisions. This means that large organizations have entered the era of data security analytics. Download here to learn more!
Tags : big data, data management, security threats, advanced analytics, security management, predictive analytics, compliance, security
     EMC Corporation
By: SAS     Published Date: Oct 18, 2017
Health insurers have long been plagued by issues of fraud, waste, abuse, error and corruption. Taking an enterprise approach to payment integrity – one that combines advanced data management and sophisticated analytics – can help payers detect and prevent fraud; effect positive change in how providers, employees and patients behave; and substantially reduce health care costs. Payers can achieve better outcomes when software support for the core disciplines of payment integrity run on a single platform.
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     SAS
By: Netezza IBM US     Published Date: Mar 27, 2012
Across all industries, Revolution R Enterprise advanced analytics platform leverages the capabilities of IBM Netezza Analytics on IBM Netezza's family of data warehouse appliances, merging high-performance, scalable data warehouse technology with advanced in-database analytics and massively parallel capabilities
Tags : ibm, technology, netezza, analytics, enterprise analytics
     Netezza IBM US
By: Adobe     Published Date: Aug 02, 2017
With the advanced analytics capabilities in Adobe Analytics and the testing and targeting capacity of Adobe Target, it’s easier than ever to realise the potential of data-driven marketing. From creating a complete view of each customer across touchpoints and along their journey, to using predictive analytics, advanced anomaly detection and machine learning to understand behaviours and needs, you can use data to plan, create and optimise the experiences that matter to you and your customers.
Tags : data management, data system, business development, software integration, resource planning, enterprise management, data collection
     Adobe
By: IBM     Published Date: Jul 23, 2015
Predict better academic outcomes with IBM SPSS Decision Management for Student Performance.
Tags : predictive analytics, performance management, student performance, spss, decision management, intervention measures, graduation rates, advanced placement courses, data analytics
     IBM
By: SAS     Published Date: Mar 06, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
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     SAS
By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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     SAS
By: SAS     Published Date: Jun 06, 2018
Today’s consumers expect immediate, personalized interactions. To meet these expectations, companies must differentiate their brands through timely, targeted and tailored customer experiences based on real-time data analytics. This report, sponsored by SAS, Intel and Accenture and conducted by Harvard Business Review Analytic Services, looks at how businesses are using advanced customer data analytics, along with real-time analytics and real-time marketing, to enhance their customers’ experiences. Learn why organizations that place a high value on real-time capabilities still struggle to achieve them, what companies can do to ensure success as they adopt and implement real-time analytics solutions, and what benefits successful companies are already seeing.
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     SAS
By: IBM     Published Date: Jul 27, 2015
Communications service providers have much to gain from deploying big data analytics capabilities that enable smarter campaigns.
Tags : ibm advanced analytics platform, big data analytics, communications service providers, analytics software, predictive analytics, analytics visualization, historical analysis
     IBM
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