Datasheets & Brochures

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Datasheets

  • Denodo Platform 5.0 - Data Virtualization | Data Services | Web Integration

    Denodo Platform 5.0 responds to the need of dealing with more data types, ubiquitous data and bigger data volumes, reducing data latencies, reducing data replication and delivering more agility and value than traditional technologies. The platform is an integrated Data Virtualization platform that creates, manages and delivers virtualized data service at both project and enterprise levels with speed, agility and high performance.

    Denodo Platform 5.0 connects to data sources - be they structured, semi-structured or unstructured, internal or external - and combines them into logical / virtual data services to provide unified access and integrated delivery through a single “virtual” data layer and publishes these to consuming applications in real-time (right-time). It includes key capabilities for real-time query optimization supported by intelligent caching and scheduled data orchestration, unified data governance and quality, and ability to deliver data services in multiple formats with managed security and service-levels.

Brochures

  • Data Virtualization for Agile Enterprise Architectures

    Organizations are rapidly adopting data virtualization to meet the need for agile integration and real-time access to growing volumes of information assets from disparate sources. The following datasheet covers the top 10 questions and answers for Data Virtualization in the Agile Enterprise Architecture and use cases that illustrate how Denodo customers use high-performance data virtualization for stand-alone projects and to add enterprise-wide data services capabilities.
  • Data Virtualization for Agile BI and Reporting

    In today's global, dynamic environment, agile and pervasive business intelligence (BI) is critical to success. Traditional approaches to BI separate transactional and analytical data through physical data replication resulting in complex, multi-tiered BI infrastructures that were not designed to be agile. Despite advances in BI technology, the traditional approach struggles to access dynamic data across disparate enterprise, Web and unstructured sources, manage growing data volumes, and enable real-time BI. Used alone or as a data warehouse extension, Data Virtualization delivers Agile BI at a fraction of the cost and time compared to traditional approaches.
  • The New Data Integration: Data Virtualization, Data Services, Data Mashups

    Leading companies leverage user-generated, partner and public data accessed through data feeds or directly from the Web, the Cloud and SaaS applications, log files, Excel, Word, PDF and other sources. Denodo's Data Virtualization makes it easy to access, normalize, cleanse, filter, structure and federate data from virtually any data source or type and allows applications to leverage them using standard query language or web services.

Solution Briefs

  • Achieve value and insight with IBM PureData for Analytics and Denodo

    Denodo´s partnership with IBM has resulted in solutions for integrating data in Pure Data System for Analytics (Netezza) and IBM's BigInsights. After extensive collaborative technical work and optimization, the performance for the Denodo Platform was tested in the IBM Labs and it exceeded expectations in all three use patterns initially contemplated to be co-marketed by IBM. These patterns are described in the IBM solution brief.
  • Data Virtualization Enables the Intelligent Digital Oil Field

    This solution brief provides examples of how leading energy customers use data virtualization to gain faster access to new sources, agile data services delivery and lower integration costs across disparate structured/unstructured well, drilling, lease, regulatory and market data. Denodo enables business agility and ROI through a unified virtual data layer for enterprise-wide information needs.
  • DBTA: Elephant Traps …
    How to Avoid Them With Data Virtualization

    Big Data is being talked about everywhere … in IT and business conferences, venture capital, legal, medical and government summits, blogs and tweets … even Fox News! The prevailing mindset is that if you don’t have a Big Data project, you’re going to be left behind. In turn, CIOs are feeling pressured to do something—anything—about Big Data. So while they are putting up Hadoop clusters and crunching some data, it seems that the really big (data) question all of them should be asking is where is the value going to come from?, what are the “real” use cases?, and finally how can they prevent this from becoming yet another money pit, or “elephant trap,” of technologies and consultants?
  • Enabling faster decision making and greater efficiency for E&P companies through a unified view of data

    Oil and gas exploration and production companies are faced with a strong need to increase efficiency of existing wells and find new assets faster so they can beat global competition and high market volatility. Companies are also realizing that leveraging information assets effectively is one of the key steps to address needs and move towards creating the ‘intelligent oil field’. So, they are looking at Data Virtualization as a key enabler in this process as it provides a unified view of all data silos and the flexibility to integrate real-time and persistent data feeds on-demand to access the most current information for decision making.
  • DBTA Best Practices: Data Virtualization is Vital for Maximizing Your NOSQL and Big Data Investment

    Growth of non-relational data technologies has continued unabated, driven by the need for faster and smarter analytics as well as the increasing size of data itself. Technical buzzwords like NOSQL and Big Data are now commonplace. But, simply throwing money and resources at the latest NOSQL or Hadoop technology won’t solve business problems by itself. Having a strategy in place is vital so your company can actually use Big Data-not merely manage it. This article addresses the benefits of having Data Virtualization as a fundamental part of any data strategy.
  • Information Superiority for Defense Intelligence

    This brief discusses how Data Virtualization enabled EU Homeland Security to build superior situation awareness and cross-border interoperability due to its ability to bring together heterogeneous information in law enforcement databases, distributed sensors, and web data into a unified data layer and publish this information in the form of flexible, secure data services to decision-support tools and analytics applications in real-time for critical intelligence updates and early warning updates of suspicious activities.
  • DBTA Best Practices: Data Virtualization - Smart Move for Higher ROA!

    Data Integration is not new ... in fact, it’s been an endless money pit! Even after spending millions, companies face data challenges that are only getting bigger. What’s missing and why? And, how do you measure the value of a new integration technology that promises the elusive “right information to the right user at the right time”? This article addresses how ROA (Return on Assets) can be considered as a metric to evaluate a return on Data Virtualization investment.
  • Data’s New Virtual Reality - Driven by Business Needs for Speed and Agility

    What if you could simply and easily analyze consolidated information from a sales data mart, a few spreadsheets and a big social media feed? How about the value you could gain from combining real-time customer behavior information with historical trend data from disparate sources to make instant, insightful decisions? For many IT shops, it’s a dream; perhaps a nightmare. For many modern businesses, it’s a necessity. For some market leaders, it’s the new Virtual Reality-a Data Virtualization reality.
  • DBTA Best Practices: Top 4 Data Challenges Addressed by Data Virtualization

    Data is now BIG! Business users have access to an unprecedented volume of data that can potentially enable them to create new products and reach new customers and markets at unbelievable speeds. But ironically, the same data poses critical challenges that stop them from getting there. This article addresses how Data Virtualization is used by companies to create a unified view of data and information to address 4 key data challenges and provide new capabilities.
  • Effective Risk Management and Compliance through a Unified View of Data

    Data Virtualization has seen increased adoption by leading investment and commercial banks, securities, insurance, and other financial services firms to provide unified data access for risk and compliance reporting with proven results. Read more to find out how Data Virtualization can be leveraged by financial institutions to help manage risk, ensure compliance and control cost.
  • Data Virtualization for Big Data: How to Choose the Right Integration Model

    Data Virtualization (DV) has gone mainstream and its maturity has driven widespread use of DV for agile business intelligence (BI) and Big Data analytics. This advertorial revisits 5 common sense best practices for using DV with Big Data and then looks more closely at the importance and impact of the Extended Relational Model.
  • Data Virtualization Unifies Data Access for Actionable BI and Agile Processes

    BI/Analytics needs to be agile, pervasive, and more actionable in the context of business processes to realize its maximum benefits. Ideally, intelligence should flow to the appropriate business process at any time, but is hindered by rigid IT architecture. The solution to achieving more actionable intelligence is to deploy a Unified Semantic Layer that delivers Virtualized Data Services for servicing the continuum of applications from BI/Analytics, Operational BI, or Operational Applications.
  • Big Data – 5 Commonsense Best Practices Point to Data Virtualization

    Neither Big Data nor the technology to access it is perfect, but Customers of Denodo are the most innovative in their industry in making full use of all information available to them—internal or external, structured or unstructured, public or private, using best-of-breed data virtualization and storage techniques. Using Data Virtualization, they can easily access and integrate diverse sources and deliver value-added, agile data services. How do they do it? Read further and find out.
  • Simplify Data Integration – From, In and For the Cloud with Data Virtualization

    Traditional data integration-physical replication of structured-only data into marts – won't do for cloud integration and is inflexible by design. Part of the Database Trends and Applications Best Practices Series in Data Cloud Computing, this paper outlines how Data Virtualization Simplifies Data Integration from, in, and for the Cloud and how Agile Data Services platforms like Denodo fill the gap, and at a much lower cost, by leveraging Data Virtualization and Web integration to unify and extend your current information architectures to embrace Cloud, SaaS, Public Web and more.
  • Pragmatic MDM – Data Virtualization Enables Simple to Complex MDM with Low Risk

    Growing Heterogeneity in database management systems and the rise of unstructured data have created a growing variety of data integration strategies at user.
  • Data Virtualization for Operational BI and Agile Reporting—Top 10 FAQs

    Business goals are relatively constant – Accelerate Revenue. Cut Costs. Lower Risk. Gain Competitive Advantage. But, achieving these goals in a global, dynamic environment requires faster ways of turning data into better decisions. Executives, operational managers and frontline employees need historical mining of warehoused data, predictive analytics of "data exhausts," real-time 360° customer views, and simple, timely, accurate operational reporting and dashboards… Successful companies have adopted Data Virtualization (DV) and Data Services solutions to access disparate data and deliver it to BI applications,middleware and end users in half the time and one-fourth the cost of traditional approaches.
  • Database Trends and Applications – Solving Key Business Problems with Enterprise Data Mashups

    To realize more value from their information and gain competitive advantage, organizations want to breach the data silos and integrate all forms of information. This paper addresses the key drivers for the need for comprehensive data integration and provides an overview along with use cases on using the Denodo platform to achieve this.
  • Data Virtualization for High Impact

    Denodo Technologies is a leader in Data Virtualization and Virtualized Data Services that offers unified data access and virtual data integration across structured and unstructured information. We help leading companies adopt alternative or hybrid approaches to traditional data integration. This provides faster results and more flexibility with options to scale to enterprise-class performance.

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