complex data

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Published By: Denodo     Published Date: Feb 27, 2019
Organizations continue to struggle with integrating data quickly enough to support the needs of business stakeholders, who need integrated data faster and faster with each passing day. Traditional data integration technologies have not been able to solve the fundamental problem, as they deliver data in scheduled batches, and cannot support many of today’s rich and complex data types. Data virtualization is a modern data integration approach that is already meeting today’s data integration challenges, providing the foundation for data integration in the future. Download this whitepaper to learn more about: The fundamental challenge for organizations today. Why traditional solutions fall short. Why data virtualization is the core solution.
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Denodo
Published By: Tamr, Inc.     Published Date: Feb 08, 2019
Traditional data management practices, such as master data management (MDM), have been around for decades – as have the approaches vendors take in developing these capabilities. And they were well-equipped for the problem at hand: managing data at modest size and complexity. However, as enterprises mature and start to view their data assets as a source of competitive advantage, new methods to managing enterprise data become desirable. Enterprises now need approaches to data management that can solve critical issues around speed and scale in an increasingly complex data environment. This paper explores how data curation technology can be used to solve data mastering challenges at scale.
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Tamr, Inc.
Published By: Databricks     Published Date: Sep 13, 2018
Learn how to get started with Apache Spark™ Apache Spark™’s ability to speed analytic applications by orders of magnitude, its versatility, and ease of use are quickly winning the market. With Spark’s appeal to developers, end users, and integrators to solve complex data problems at scale, it is now the most active open source project with the big data community. With rapid adoption by enterprises across a wide range of industries, Spark has been deployed at massive scale, collectively processing multiple petabytes of data on clusters of over 8,000 nodes. If you are a developer or data scientist interested in big data, learn how Spark may be the tool for you. Databricks is happy to present this ebook as a practical introduction to Spark. Download this ebook to learn: • Spark’s basic architecture • Why Spark is a popular choice for data analytics • What tools and features are available • How to get started right away through interactive sample code
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Databricks
Published By: Access Sciences     Published Date: Sep 07, 2014
Few organizations have fully integrated the role of the Data Steward due to concerns about additional project complexity, time away from other responsibilities or insufficient value in return. The principles of the Agile methodology (whether or not Agile is followed for projects) can offer guidance in making the commitment to designating and empowering the Data Steward role. By placing insightful people in a position to connect innovators, respond to change and spur development aligned with business activities, organizations can expect to see a more efficient and effective use of their information assets.
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Access Sciences
Published By: Melissa Data     Published Date: Jan 18, 2018
Maintaining high quality data is essential for operational efficiency, meaningful analytics and good long-term customer relationships. But, when dealing with multiple sources of data, data quality becomes complex, so you need to know when you should build a custom data quality tools over canned solutions. To answer this question, it is important to understand the difference between rules-based data quality, where internal subject matter expertise is necessary – and active data quality, where different domain expertise and resources are required.
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Melissa Data
Published By: AnalytixDS     Published Date: Feb 28, 2015
With future business intelligence solutions clearly evolving from data that comes from highly efficient and well behaved systems, to data that comes from the extended enterprise where data is not necessarily so well structured and behaved - Organizations are forced into a more collaborative mode of operation with their core infrastructure being adapted from the consumer space, and to the extent possible, conformed to their existing repositories. This whitepaper attempts to address various challenges consumers face while managing enormous data sets within the context of this complex scenario. Further, we’ll try to answer the question: Is Big Data Governance really that different from traditional data governance initiatives? Finally, we’ll see how AnalytiX™ Mapping Manager™ can help organizations accelerate the development and deployment of a successful Big Data/ Business Intelligence platform and accelerate delivery of all sorts of data – structured, semi-structured as well as unstruc
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big data, big data governance, data governance, analytixds
    
AnalytixDS
Published By: Reltio     Published Date: Aug 11, 2017
"Forrester's research uncovered a market in which Reltio [and other companies] lead the pack,” the Forrester Wave Master Data Management, 2016 states. "Leaders demonstrated extensive and MDM capabilities for sophisticated master data scenarios, large complex ecosystems, and data governance to deliver enterprise-scale business value.”
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Reltio
Published By: Reltio     Published Date: May 22, 2018
"Forrester's research uncovered a market in which Reltio [and other companies] lead the pack,” the Forrester Wave Master Data Management states. "Leaders demonstrated extensive and MDM capabilities for sophisticated master data scenarios, large complex ecosystems, and data governance to deliver enterprise-scale business value.” Reltio executes the vision for next-generation MDM by converging trusted data management with business insight solutions at scale and in the cloud. Machine learning and graph technology capabilities enable a contextual data model while also maintaining temporal and lineage changes of the master data.
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Reltio
Published By: Silwood Technology     Published Date: Nov 28, 2016
Business functions in large organizations are usually handled by software application packages. Some of the most well-known of these are from SAP, Oracle, Salesforce and Microsoft. These packages all store their data in a database. Often however it is necessary to use that data with other IT projects. In this instance being able to understand the metadata that defines these databases is critical. The challenge is that their metadata is complex, opaque and difficult to access. This paper describes how the top application packages store and use their own metadata. It explores the importance of understanding that metadata and examines the obstacles in getting at that metadata in a timely and effective manner.
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Silwood Technology
Published By: Silwood Technology     Published Date: Mar 21, 2017
Business functions in large organizations are usually handled by software application packages. Some of the most well-known of these are from SAP, Oracle, Salesforce and Microsoft. These packages all store their data in a database. Often however it is necessary to use that data with other IT projects. In this instance being able to understand the metadata that defines these databases is critical. The challenge is that their metadata is complex, opaque and difficult to access. This paper describes how the top application packages store and use their own metadata. It explores the importance of understanding that metadata and examines the obstacles in getting at that metadata in a timely and effective manner.
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Silwood Technology
Published By: FairCom     Published Date: May 25, 2016
As companies embrace NoSQL as the “next big thing,” they are rightly cautious of abandoning their investment in SQL. The question a responsible developer or IT manager must investigate is “in which cases are each of these technologies, SQL and NoSQL, the appropriate solution?” For example, cloud provider BigStep offered this assessment: “NoSQL is not the best model for OLTP, ad hoc queries, complicated relationships among the data, and situations when stability and reliability outweigh the importance of speed.” While that statement may be true of many NoSQL databases, c-treeACE is the exception. Its unique, No+SQL architecture offers the advantages of SQL on top of a robust, high-performance NoSQL core engine. In this white paper, you'll read five ways c-treeACE breaks the NoSQL mold in terms of: • Data Integrity • Availability and Reliability • Complex Data Relationships • Flexible Queries • Performance
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FairCom
Published By: Deloitte Process Robotics     Published Date: May 04, 2018
Deloitte Process Robotics (DPR) solutions use a lightweight approach to train ‘bots’ that automate repetitive tasks of medium complexity without changes to existing process or IT infrastructure. With ever-growing repositories of unanalyzed and underutilized data, organizations require highly flexible and scalable enterprise data management (EDM) processes, DPR makes it possible for organizations to adopt comprehensive yet affordable EDM processes in the Big Data Era, helping organizations transform data into strategic assets through the automation of capabilities.
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Deloitte Process Robotics
Published By: Io-Tahoe     Published Date: Jan 15, 2019
The white paper addresses the problem of managing data in an increasingly complex, hybrid and distributed world; acknowledging that it is too great even for highly-skilled analysts and scientists to handle alone. To solve this problem, organizations should understand why a single unified product from smart data discovery to AI-driven data catalog can vastly reduce the time it takes to do the kind of analytics that are necessary for digital transformation.
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Io-Tahoe
Published By: Embarcadero     Published Date: Apr 02, 2014
IT professionals in organizations developing an enterprise data modeling program may feel overwhelmed at the scope and complexity of initiating new methods, tools, and techniques. Whether their organization is just starting out or experienced in enterprise data modeling efforts, there are certain pitfalls that can become obstacles to success. This paper looks at the benefits of an effective enterprise data modeling effort and discusses seven common mistakes that organizations can make in developing enterprise data models.
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Embarcadero
Published By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
Discover how HPE is responding to the massive growth in enterprise data with intelligent storage. Data helps enterprises find new ways to reach and serve customers to grow profitability, but only when it is available at the right place and the right time. The growing complexity of managing and securing data prevents businesses from gaining its full value. Hewlett Packard Enterprise delivers the world’s most intelligent storage for the hybrid cloud world by providing storage that is driven by artificial intelligence, built for the cloud, and delivered as a service.
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Hewlett Packard Enterprise
Published By: Hitachi Vantara     Published Date: Mar 08, 2019
Finding the right data protection and recovery solution for complex enterprise infrastructures is a formidable challenge. Traditional backup and recovery solutions cannot keep up with or meet today’s business-critical requirements. Read this white paper to learn smarter approaches to data protection and recovery. See how to radically improve key performance metrics – including business continuity – as well as backup windows, operational recovery and disaster recovery.
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Hitachi Vantara
Published By: Alibaba Cloud SEA     Published Date: Mar 11, 2019
Many businesses are adopting a multi-cloud infrastructure. However, managing data and communication between multiple cloud environments is often challenging and complex. Therefore, companies often try to find a technical partner that can help them. Companies with on-premise data centers need some type of interconnect to access their products and services hosted on the cloud. The traditional Virtual Private Network (VPN) connection method usually can’t meet enterprise speed,stability, security, and compliance requirements.This whitepaper describes the challenges that companies face when building dedicated connections between different cloud environments and how Alibaba Cloud’s Express Connect is the perfect solution for them
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data center, cloud computing, networking, security, china, global expansion
    
Alibaba Cloud SEA
Published By: TIBCO Software APAC     Published Date: Feb 14, 2019
Digital business initiatives have expanded in scope and complexity as companies have increased the rate of digital innovation to capture new market opportunities. As applications built using fine-grained microservices and functions become pervasive, many companies are seeing the need to go beyond traditional API management to execute new architectural patterns and use cases. APIs are evolving both in the way they are structured and in how they are used, to not only securely expose data to partners, but to create ecosystems of internal and/or third-party developers. In this datasheet, learn how you can use TIBCO Cloud™ Mashery® to: Create an internal and external developer ecosystem Secure your data and scale distribution Optimize and manage microservices Expand your partner network Run analytics on your API performance
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TIBCO Software APAC
Published By: Apstra     Published Date: Feb 21, 2019
Modern data centers based on hyperscale, leaf-spine switching architectures are growing so large and complex they are outstripping the capacity of operators to engineer, configure and manage these networks using traditional tools and techniques. As a result, data center operators are looking for new ways to automate workflows, maximize uptime and increase operational agility while reducing operating costs
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acg, data center efficiency
    
Apstra
Published By: Attivio     Published Date: Aug 20, 2010
Current methods for accessing complex, distributed information delay decisions and, even worse, provide incomplete insight. This paper details the impact of Unified Information Access (UIA) in improving the agility of information-driven business processes by bridging information silos to unite content and data in one index to power solutions and applications that offer more complete insight.
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attivio, data warehouse, unified information, data, content, unstructured content, integration, clob, blob, database development, data warehousing
    
Attivio
Published By: ASG Software Solutions     Published Date: Jul 20, 2009
Managing service delivery in todayís complex and dynamic business environments demands new and different approaches from IT. The explosive growth and the rate of change of information has brought particularly daunting challenges for IT that have contributed to incredibly complex underlying infrastructures. To get a true picture of all of the components necessary to support an IT or Business Service, you must access and bring together data that resides in disparate data silos throughout the enterprise.
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asg, sla, cmdb, bsm, metadata, itsm, metacmdb, lob, ecommerce, bpm, workflow, itil, cmdmdb, service optimization, analytical applications, business intelligence, database development, data integration
    
ASG Software Solutions
Published By: Spectrum Enterprise     Published Date: Feb 07, 2018
How Fiber Powers Growth – An Expert Q&A Guide provided by Spectrum Enterprise. Businesses today need bandwidth capacity to handle complex applications and ever-increasing data. See how technology experts rely on fiber to increase productivity and provide stronger growth opportunities.
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Spectrum Enterprise
Published By: HPE & Intel®     Published Date: Oct 10, 2016
In the financial services industry (FSI), high-performance compute infrastructure is not optional; it’s a prerequisite for survival. No other industry generates more data, and few face the combination of challenges that financial services does: a rapidly changing competitive landscape, a complex regulatory environment, tightening margin pressure, exponential data growth, and demanding performance service-level agreements (SLAs).
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HPE & Intel®
Published By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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Cisco
Published By: HERE Technologies     Published Date: Jan 22, 2019
Rising urbanization has brought unprecedented levels of traffic and congestion to our major towns and cities. Departments of transport are battling to ensure their regions aren’t negatively impacted by increased pressure on their road networks. On the frontline are traffic operators and planners. Every day, they face complex challenges as they attempt to improve traffic flow, minimize incidents, and unearth solutions to network issues. This eBook explains how traffic planners and operators can use data to help overcome some of the challenges they face.
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public sector, urbanization, traffic management
    
HERE Technologies
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