advanced data analytics

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Data Lakes, Purposes, Practices, Patterns and Platforms

Published 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

IBM Analytic Answers for Retail Purchase Analysis and Offer Targeting

Published 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.
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ibm analytics answers, retail purchase, offer targeting, infrastructure, offer, ibm, software licenses
    
IBM

On Demand Webcast: Activate Cloud Storage to Improve Storage Environment Efficiency

Published 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.
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ibm, cloud, cloud storage, storage, storage environment efficiency, environment efficiency, data protection, data driven analytics, storage systems, storage costs, it budget, it management, database security, cloud computing, infrastructure
    
IBM

Activate Cloud Storage to Improve Storage Environment

Published 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.
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cloud computing, it efficiency, cloud storage, data protection, it management, data management, virtualization
    
IBM

Activate Cloud Storage to Improve Storage Environment

Published 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.
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storage environment, cloud storage, it efficiency, cloud agility, data-driven analytics, it management, knowledge management, enterprise applications, data management
    
IBM

TDWI Best Practices: Data Lakes, Purposes, Practices, Patterns and Platforms (customized reports)

Published 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

NEC Directs Attention to Solve Server Side Stress

Published 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.
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servers, virtualization, customer value, analytics, application owners, system integrators, big data, reliability, enterprise, availability, serviceability, processor, architecture, express, stress, data management, application integration, productivity
    
NEC

Critical Capabilities for Analytics and Business Intelligence Platforms

Published 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

Buyer's Criteria for Advanced Malware Protection

Published 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
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protection, analytics, global security, intelligence, virtual, gateway, attacks, malware, big data, security, data management
    
Cisco

Finding the Path to Security in the Big Data Landscape

Published 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.
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security, big data, ibm, data protection
    
IBM

Inside BIGDATA Guide to Predictive Analytics

Published 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

Inside BIGDATA Guide to Predictive Analytics

Published 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

Inside BIGDATA Guide to Predictive Analytics

Published 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

Moving finance forward with advanced data analytics.

Published 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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