Big Data Analytics Market Study

Based on survey methodology, this second Big Data Analytics Market Study from Dresner Advisory focuses upon the combination of analytical solutions within the Hadoop ecosystem, adding some new criteria and exploring changing market dynamics and user perceptions and plans.

You’ll also learn why Pentaho ranked among the top three Big Data Analytic vendors in the areas of infrastructure, data access, search, machine learning, and supported distributions.

Read the market study to learn:

  • Top infrastructure choices, machine learning technologies and vendors for big data
  • Ratings of technologies and platforms used in big data analytics
  • Big data trends by industries, functions, and geographical regions
  • The most popular big data use cases

*Pentaho, a Hitachi Group company, helps organizations harness value from all their data. Our open enterprise-class platform provides end-to-end data preparation, integration, and analytics.

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Konzepte für den Erfolg mit Big Data

Erfahren Sie, wie Sie mit vier gängigen Big Data-Szenarios erfolgreich sein können: Data Warehouse-Optimierung, optimierte Datenaufbereitung, 360-Grad-Ansicht von Kunden, Monetarisierung von Daten.

Folgende Themen werden behandelt:

  • Wie Sie Data Warehouse-Kosten reduzieren und die Leistung verbessern
  • Wie mit einem agilen Datenintegrationsprozess die Entwicklungszeit für mapReduce um das 15-Fache gegenüber herkömmlichen Programmier- und Skripterstellungsverfahren reduziert werden kann
  • Wie durch die Verknüpfung verschiedener operativer und Transaktions-Datenquellen zur Erstellung von On-Demand-Analyseansichten neue Wachstumsmöglichkeiten erschlossen werden können
  • Wie durch die Verwendung interner Daten hochwertige Datensets für externe Kunden bereitgestellt werden können
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Plans d’action pour une mise en oeuvre réussie des Big Data

Découvrez comment réussir avec quatre scénarios Big Data courants : Optimiser l’entrepôt de données, Optimiser une « raffinerie » de données, Avoir une vue à 360° des clients et Monétiser mes données.

Sommaire :

  • Comment réduire le coût d’entreposage des données et améliorer les performances ?
  • Comment la souplesse d’intégration des données permet-elle de diviser par 15 le temps de développement mapReduce par rapport aux processus manuels classiques de codage et d’écriture de scripts ?
  • En quoi le mélange de plusieurs sources de données opérationnelles et transactionnelles permettant de créer, à la demande, une vue analytique de vos principaux points de contact client vous aide-t-il à réduire la perte de clients et à identifier de nouvelles opportunités de revenus ?
  • Comment est-il possible d’utiliser des données internes pour proposer à des clients externes des jeux de données à forte valeur ajoutée ?
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TDWI Best Practices Report: Improving Data Preparation for Business Analytics: (Sponsored by Pentaho*)

Want to get the data you need faster? If you’re trying to automate and scale your data preparation processes, this TDWI Best Practices Report is a must-read.

The TDWI report also examines how self-service data preparation will affect your operations, including how self-service data prep fits with visual analytics, data discovery, BI tools, and Hadoop.

Read the TDWI best practices report to learn how to:

  • Establish smarter, more scalable, and better coordinated data prep processes
  • Reduce the burden on IT through self-service, while ensuring data is appropriately governed
  • Make better data-driven decisions
  • Use the best of old and new worlds, leveraging data warehouses and Hadoop at the same time

*Pentaho, a Hitachi Group company, helps organizations harness value from all their data. Our open enterprise-class platform provides end-to-end data preparation, integration, and analytics.

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Faster, More Accurate Decisions with IT Analytics

The rise of the digital enterprise has created an explosion of valuable, yet unharnessed data for IT organizations. Traditional IT tools and processes, founded on the notion of control and management, are unable to support the speed and agility requirements of the digital enterprise. IT organizations must reengineer their approach from traditional analytics and reporting to adaptive, real-time digital service analytics.

Take more accurate decisions with IT Analytics, download this paper.

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Go Beyond Mere Monitoring

We live in an always-on world. We are quick to adopt new technology and quick to abandon it if slow or unresponsive. This mobile-consumer mindset has created significant challenges for IT: ensure customer satisfaction by proactively monitoring performance and availability, identify web application problems, predict the performance of the application and measure service levels. TrueSight App provides all of them.

Download this paper: keep users happy and applications healthy.

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Innovation Insight for Collective Intelligence Benchmarking

Collective Intelligence Benchmarking (CIB) is a new, efficient approach that extracts insights from massive data sets to provide an understanding of end-user experience. This report from Gartner highlights cloud and network monitoring solutions that apply CIB techniques, enabling IT teams to quickly identify performance issues and ultimately "hold cloud- and SaaS-based providers accountable for below-par service delivery."
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Drive Data to Decision

In this eBook, we look at the rapidly evolving use of advanced analytics in defense intelligence. The concept of advanced analytics comes alive in a study of Operation Nighthawk, a multinational training exercise that tested the abilities of data analytic tools to support tactical operations.
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Adapt to Digital Business with Single System Image (SSI) Monitoring Capabilities for Mainframes

Meet the demand for performance and availability with simpler mainframe monitoring.

Finding and resolving issues is critical to keep revenue-generating digital services running their best. In this paper, you’ll learn how to achieve a single, simpler view across your mainframe environment before performance and availability issues impact your business.

Read the white paper to:

  • Improve the efficiency and productivity of mainframe staff
  • Maintain performance despite growing complexity
  • Shrink MTTR, reduce system outages and lower TCO

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