advanced data analytics

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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
By: IBM     Published Date: Apr 14, 2016
Advanced analytics can provide extremely valuable 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, data analytics, analytics, media, entertainment
     IBM
By: SAS     Published Date: Aug 28, 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. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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     SAS
By: IBM     Published Date: Apr 04, 2013
Many small and midsize retailers could benefit from using advanced analytics to understand their customers better and improve promotions but are daunted by the prospect. They are aware that advanced analytics can help retailers turn purchase data into retail excellence. However, they perceive that advanced analytics requires massive infrastructure changes, expensive software licenses, analytics expertise, long lead times and major upfront capital expenses.
Tags : ibm analytics answers, retail purchase, offer targeting, infrastructure, offer, ibm, software licenses
     IBM
By: IBM     Published Date: Jul 22, 2014
Join this session to learn how you can quickly convert existing storage to Cloud storage, standardize advanced data protection capabilities, and utilize advanced data-driven analytics to optimize tiering across storage systems --- reducing per unit storage costs up to 50% and freeing up valuable IT budget.
Tags : ibm, cloud, cloud storage, storage, storage environment efficiency, environment efficiency, data protection, data driven analytics, storage systems, storage costs, it budget, it management
     IBM
By: IBM     Published Date: Nov 04, 2014
Organizations are shifting to Cloud to improve agility, reduce costs and increase IT efficiency. To achieve the benefits promised by Cloud, your storage infrastructure needs to be virtualized and provide the required automation and management capabilities. Join this session to learn how you can quickly convert existing storage to Cloud storage, standardize advanced data protection capabilities, and utilize advanced data-driven analytics to optimize tiering across storage systems --- reducing per unit storage costs up to 50% and freeing up valuable IT budget.
Tags : cloud computing, it efficiency, cloud storage, data protection, it management, data management
     IBM
By: IBM     Published Date: Jan 23, 2015
Organizations are shifting to Cloud to improve agility, reduce costs and increase IT efficiency. To achieve the benefits promised by Cloud, your storage infrastructure needs to be virtualized and provide the required automation and management capabilities. Watch this webinar to learn how you can quickly convert existing storage to Cloud storage, standardize advanced data protection capabilities, and utilize advanced data-driven analytics to optimize tiering across storage systems --- reducing per unit storage costs up to 50% and freeing up valuable IT budget.
Tags : storage environment, cloud storage, it efficiency, cloud agility, data-driven analytics, it management, enterprise applications, data management
     IBM
By: SAS     Published Date: Oct 18, 2017
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. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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     SAS
By: NEC     Published Date: Aug 12, 2014
NEC has introduced the Express5800/A2000 Series Servers to accommodate enterprise application demands with peak server reliability, availability, and serviceability. The new server architecture and NEC engineering functionality align well with many of the most important IT priorities in 2014, including virtualization, big data and advanced data analytics. With the Express5800/A2000 Servers, NEC has the opportunity to educate application owners and work with system integrators to drive awareness and ultimately investment in its new server platform, which will help drive customer value. In this white paper, you will learn how these next-generation servers from NEC are ready to accommodate some of today’s demanding workloads.
Tags : servers, virtualization, customer value, analytics, application owners, system integrators, big data, reliability, enterprise, availability, serviceability, processor, architecture, express, stress, data management
     NEC
By: MicroStrategy     Published Date: Apr 11, 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: Cisco     Published Date: Apr 08, 2015
This document will identify the essential capabilities you should seek in an advanced malware protection solution, the key questions you should ask your advanced malware protection vendor, and shows you how Cisco combats today’s advanced malware attacks using a combination of four techniques: ? Big data analytics ? Collective global security intelligence ? Enforcement across multiple form factors (networks, endpoints, mobile devices, secure gateways, and virtual systems) ? Continuous analysis and retrospective security
Tags : protection, analytics, global security, intelligence, virtual, gateway, attacks, malware, big data, security, data management
     Cisco
By: IBM     Published Date: Oct 16, 2017
This white paper examines how some of the ways organizations use big data make their infrastructures vulnerable to attack. It presents recommended best practices organizations can adopt to help make their infrastructures and operations more secure. And it discusses how adding advanced security software solutions from IBM to their big-data environment can fill gaps that big-data platforms by themselves do not address. It describes how IBM® Security Guardium®, an end-to- end solution for regulatory compliance and comprehensive data security, supports entitlement reporting; user-access and activity monitoring; advanced risk analytics and real-time threat detection analytics; alerting, blocking, encryption and other data protection capabilities, as well as automated compliance workflows and reporting capabilities, to stop threats.
Tags : security, big data, ibm, data protection
     IBM
By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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     TIBCO Software
By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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     TIBCO Software
By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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     TIBCO Software
By: Workday APAC     Published Date: Dec 11, 2018
Our latest global survey revealed a number of barriers between finance and analytics. See what separates finance leaders from data intelligence.
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     Workday APAC
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